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ORCIDMichael M. Bronstein
Person information
- affiliation: University of Oxford, UK
- affiliation: Twitter
- affiliation: Imperial College London, Department of Computing, UK
- affiliation: Technion - Israel Institute of Technology, Haifa, Israel
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2020 – today
- 2025
[j71]Luca Cosmo, Giorgia Minello, Alessandro Bicciato
, Michael M. Bronstein, Emanuele Rodolà, Luca Rossi, Andrea Torsello:
Graph Kernel Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 36(4): 6257-6270 (2025)- [c164]Jianan Zhao, Zhaocheng Zhu, Mikhail Galkin, Hesham Mostafa, Michael M. Bronstein, Jian Tang:
Fully-inductive Node Classification on Arbitrary Graphs. ICLR 2025 - [c163]Jacob Bamberger, Federico Barbero, Xiaowen Dong, Michael M. Bronstein:
Bundle Neural Network for message diffusion on graphs. ICLR 2025 - [c162]Linus Bao, Emily Jin, Michael M. Bronstein, Ismail Ilkan Ceylan, Matthias Lanzinger:
Homomorphism Counts as Structural Encodings for Graph Learning. ICLR 2025 - [c161]Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T. Law, Xiaowen Dong, Michael M. Bronstein:
Neural Spacetimes for DAG Representation Learning. ICLR 2025 - [c160]Yam Eitan, Yoav Gelberg, Guy Bar-Shalom, Fabrizio Frasca, Michael M. Bronstein, Haggai Maron:
Topological Blindspots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity. ICLR 2025 - [c159]Arne Schneuing, Ilia Igashov, Adrian W. Dobbelstein, Thomas Castiglione, Michael M. Bronstein, Bruno Correia:
Multi-domain Distribution Learning for De Novo Drug Design. ICLR 2025 - [c158]Joshua Southern, Francesco Di Giovanni, Michael M. Bronstein, Johannes F. Lutzeyer:
Understanding Virtual Nodes: Oversquashing and Node Heterogeneity. ICLR 2025 - [i150]Joshua Southern, Yam Eitan, Guy Bar-Shalom, Michael M. Bronstein, Haggai Maron, Fabrizio Frasca:
Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality. CoRR abs/2501.03113 (2025) - [i149]Alvaro Arroyo, Alessio Gravina, Benjamin Gutteridge, Federico Barbero, Claudio Gallicchio, Xiaowen Dong, Michael M. Bronstein, Pierre Vandergheynst:
On Vanishing Gradients, Over-Smoothing, and Over-Squashing in GNNs: Bridging Recurrent and Graph Learning. CoRR abs/2502.10818 (2025) - [i148]Xingyue Huang, Pablo Barceló, Michael M. Bronstein, Ismail Ilkan Ceylan, Mikhail Galkin, Juan L. Reutter, Miguel Romero:
How Expressive are Knowledge Graph Foundation Models? CoRR abs/2502.13339 (2025) - [i147]Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca, Luis Müller, Jan Tönshoff, Antoine Siraudin, Viktor Zaverkin, Michael M. Bronstein, Mathias Niepert, Bryan Perozzi, Mikhail Galkin, Christopher Morris:
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks. CoRR abs/2502.14546 (2025) - [i146]Charlie B. Tan, Avishek Joey Bose, Chen Lin, Leon Klein, Michael M. Bronstein, Alexander Tong:
Scalable Equilibrium Sampling with Sequential Boltzmann Generators. CoRR abs/2502.18462 (2025) - [i145]Huidong Liang, Haitz Sáez de Ocáriz Borde, Baskaran Sripathmanathan, Michael M. Bronstein, Xiaowen Dong:
Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement. CoRR abs/2503.09008 (2025) - [i144]Federico Barbero, Alvaro Arroyo, Xiangming Gu, Christos Perivolaropoulos, Michael M. Bronstein, Petar Velickovic, Razvan Pascanu:
Why do LLMs attend to the first token? CoRR abs/2504.02732 (2025) - 2024
- [j70]Ilia Igashov, Hannes Stärk, Clément Vignac, Arne Schneuing, Victor Garcia Satorras, Pascal Frossard, Max Welling, Michael M. Bronstein, Bruno E. Correia:
Equivariant 3D-conditional diffusion model for molecular linker design. Nat. Mac. Intell. 6(4): 417-427 (2024) - [j69]Arne Schneuing, Charles Harris, Yuanqi Du, Kieran Didi, Arian Rokkum Jamasb, Ilia Igashov, Weitao Du, Carla P. Gomes, Tom L. Blundell, Pietro Lio, Max Welling, Michael M. Bronstein, Bruno E. Correia:
Structure-based drug design with equivariant diffusion models. Nat. Comput. Sci. 4(12): 899-909 (2024) - [j68]Francesco Di Giovanni, T. Konstantin Rusch, Michael M. Bronstein, Andreea Deac, Marc Lackenby, Siddhartha Mishra, Petar Velickovic:
How does over-squashing affect the power of GNNs? Trans. Mach. Learn. Res. 2024 (2024) - [c157]Federico Barbero, Ameya Velingker, Amin Saberi, Michael M. Bronstein, Francesco Di Giovanni:
Locality-Aware Graph Rewiring in GNNs. ICLR 2024 - [c156]Claudio Battiloro, Indro Spinelli, Lev Telyatnikov, Michael M. Bronstein, Simone Scardapane, Paolo Di Lorenzo:
From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module. ICLR 2024 - [c155]Avishek Joey Bose, Tara Akhound-Sadegh, Guillaume Huguet, Kilian Fatras, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael M. Bronstein, Alexander Tong:
SE(3)-Stochastic Flow Matching for Protein Backbone Generation. ICLR 2024 - [c154]Ilia Igashov, Arne Schneuing, Marwin H. S. Segler, Michael M. Bronstein, Bruno E. Correia:
RetroBridge: Modeling Retrosynthesis with Markov Bridges. ICLR 2024 - [c153]Christopher Morris, Fabrizio Frasca, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka:
Position: Future Directions in the Theory of Graph Machine Learning. ICML 2024 - [c152]Ben Finkelshtein, Xingyue Huang, Michael M. Bronstein, Ismail Ilkan Ceylan:
Cooperative Graph Neural Networks. ICML 2024 - [c151]Emily Jin, Michael M. Bronstein, Ismail Ilkan Ceylan, Matthias Lanzinger:
Homomorphism Counts for Graph Neural Networks: All About That Basis. ICML 2024 - [c150]Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Lio, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T. Schaub, Petar Velickovic, Bei Wang, Yusu Wang, Guo-Wei Wei, Ghada Zamzmi:
Position: Topological Deep Learning is the New Frontier for Relational Learning. ICML 2024 - [c149]Oscar Davis, Samuel Kessler, Mircea Petrache, Ismail Ilkan Ceylan, Michael M. Bronstein, Avishek Joey Bose:
Fisher Flow Matching for Generative Modeling over Discrete Data. NeurIPS 2024 - [c148]Ben Finkelshtein, Ismail Ilkan Ceylan, Michael M. Bronstein, Ron Levie:
Learning on Large Graphs using Intersecting Communities. NeurIPS 2024 - [c147]Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael M. Bronstein, Alexander Tong, Avishek Joey Bose:
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Generation. NeurIPS 2024 - [c146]Kacper Kapusniak, Peter Potaptchik, Teodora Reu, Leo Zhang, Alexander Tong, Michael M. Bronstein, Avishek Joey Bose, Francesco Di Giovanni:
Metric Flow Matching for Smooth Interpolations on the Data Manifold. NeurIPS 2024 - [c145]Charlie Tan, Inés García-Redondo, Qiquan Wang, Michael M. Bronstein, Anthea Monod:
On the Limitations of Fractal Dimension as a Measure of Generalization. NeurIPS 2024 - [c144]Teodora Reu, Francisco Vargas, Anna Kerekes, Michael M. Bronstein:
To smooth a cloud or to pin it down: Expressiveness guarantees and insights on score matching in denoising diffusion models. UAI 2024: 3094-3120 - [c143]Haitao Mao, Jianan Zhao, Xiaoxin He, Zhikai Chen, Qian Huang, Zhaocheng Zhu, Jian Tang, Michael M. Bronstein, Xavier Bresson, Bryan Hooi, Haiyang Zhang, Xianfeng Tang, Luo Chen, Jiliang Tang:
The 1st International Workshop on Graph Foundation Models (GFM). WWW (Companion Volume) 2024: 1789-1792 - [i143]Gbètondji J.-S. Dovonon, Michael M. Bronstein, Matt J. Kusner:
Setting the Record Straight on Transformer Oversmoothing. CoRR abs/2401.04301 (2024) - [i142]Christopher Morris, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Fabrizio Frasca, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka:
Future Directions in Foundations of Graph Machine Learning. CoRR abs/2402.02287 (2024) - [i141]Xingyue Huang, Miguel A. Romero Orth, Pablo Barceló, Michael M. Bronstein, Ismail Ilkan Ceylan:
Link Prediction with Relational Hypergraphs. CoRR abs/2402.04062 (2024) - [i140]Chen Lin, Liheng Ma, Yiyang Chen, Wanli Ouyang, Michael M. Bronstein, Philip H. S. Torr:
Revealing Decurve Flows for Generalized Graph Propagation. CoRR abs/2402.08480 (2024) - [i139]Emily Jin, Michael M. Bronstein, Ismail Ilkan Ceylan, Matthias Lanzinger:
Homomorphism Counts for Graph Neural Networks: All About That Basis. CoRR abs/2402.08595 (2024) - [i138]Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Liò, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T. Schaub, Petar Velickovic, Bei Wang, Yusu Wang, Guo-Wei Wei, Ghada Zamzmi:
Position Paper: Challenges and Opportunities in Topological Deep Learning. CoRR abs/2402.08871 (2024) - [i137]Maksym Korablyov, Cheng-Hao Liu, Moksh Jain, Almer M. van der Sloot, Eric Jolicoeur, Edward Ruediger, Andrei Cristian Nica, Emmanuel Bengio, Kostiantyn Lapchevskyi, Daniel St-Cyr, Doris Alexandra Schuetz, Victor Ion Butoi, Jarrid Rector-Brooks, Simon Blackburn, Leo Feng, Hadi Nekoei, Sai Krishna Gottipati, Priyesh Vijayan, Prateek Gupta, Ladislav Rampásek, Sasikanth Avancha, Pierre-Luc Bacon, William L. Hamilton, Brooks Paige, Sanchit Misra, Stanislaw Kamil Jastrzebski, Bharat Kaul, Doina Precup, José Miguel Hernández-Lobato, Marwin H. S. Segler, Michael M. Bronstein, Anne Marinier, Mike Tyers, Yoshua Bengio:
Generative Active Learning for the Search of Small-molecule Protein Binders. CoRR abs/2405.01616 (2024) - [i136]Joshua Southern, Francesco Di Giovanni, Michael M. Bronstein, Johannes F. Lutzeyer:
Understanding Virtual Nodes: Oversmoothing, Oversquashing, and Node Heterogeneity. CoRR abs/2405.13526 (2024) - [i135]Nian Liu, Xiaoxin He, Thomas Laurent, Francesco Di Giovanni, Michael M. Bronstein, Xavier Bresson:
Advancing Graph Convolutional Networks via General Spectral Wavelets. CoRR abs/2405.13806 (2024) - [i134]Oscar Davis, Samuel Kessler, Mircea Petrache, Ismail Ilkan Ceylan, Michael M. Bronstein, Avishek Joey Bose:
Fisher Flow Matching for Generative Modeling over Discrete Data. CoRR abs/2405.14664 (2024) - [i133]Kacper Kapusniak, Peter Potaptchik, Teodora Reu, Leo Zhang, Alexander Tong, Michael M. Bronstein, Avishek Joey Bose, Francesco Di Giovanni:
Metric Flow Matching for Smooth Interpolations on the Data Manifold. CoRR abs/2405.14780 (2024) - [i132]T. Konstantin Rusch, Nathan Kirk, Michael M. Bronstein, Christiane Lemieux, Daniela Rus:
Message-Passing Monte Carlo: Generating low-discrepancy point sets via Graph Neural Networks. CoRR abs/2405.15059 (2024) - [i131]Jacob Bamberger, Federico Barbero, Xiaowen Dong, Michael M. Bronstein:
Bundle Neural Networks for message diffusion on graphs. CoRR abs/2405.15540 (2024) - [i130]Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael M. Bronstein, Alexander Tong, Avishek Joey Bose:
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation. CoRR abs/2405.20313 (2024) - [i129]Jianan Zhao, Hesham Mostafa, Mikhail Galkin, Michael M. Bronstein, Zhaocheng Zhu, Jian Tang:
GraphAny: A Foundation Model for Node Classification on Any Graph. CoRR abs/2405.20445 (2024) - [i128]Ben Finkelshtein, Ismail Ilkan Ceylan, Michael M. Bronstein, Ron Levie:
Learning on Large Graphs using Intersecting Communities. CoRR abs/2405.20724 (2024) - [i127]Charlie Tan, Inés García-Redondo, Qiquan Wang, Michael M. Bronstein, Anthea Monod:
On the Limitations of Fractal Dimension as a Measure of Generalization. CoRR abs/2406.02234 (2024) - [i126]Baskaran Sripathmanathan, Xiaowen Dong, Michael M. Bronstein:
On the Impact of Sample Size in Reconstructing Noisy Graph Signals: A Theoretical Characterisation. CoRR abs/2406.16816 (2024) - [i125]Yam Eitan, Yoav Gelberg, Guy Bar-Shalom, Fabrizio Frasca, Michael M. Bronstein, Haggai Maron:
Topological Blind Spots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity. CoRR abs/2408.05486 (2024) - [i124]Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T. Law, Xiaowen Dong, Michael M. Bronstein:
Neural Spacetimes for DAG Representation Learning. CoRR abs/2408.13885 (2024) - [i123]Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng, Zachary Quinn, Cheng-Hao Liu, Sarthak Mittal, Nouha Dziri, Michael M. Bronstein, Yoshua Bengio, Pranam Chatterjee, Alexander Tong, Avishek Joey Bose:
Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction. CoRR abs/2410.08134 (2024) - [i122]Ahmed A. A. Elhag, T. Konstantin Rusch, Francesco Di Giovanni, Michael M. Bronstein:
Relaxed Equivariance via Multitask Learning. CoRR abs/2410.17878 (2024) - [i121]Linus Bao, Emily Jin, Michael M. Bronstein, Ismail Ilkan Ceylan, Matthias Lanzinger:
Homomorphism Counts as Structural Encodings for Graph Learning. CoRR abs/2410.18676 (2024) - [i120]Haitz Sáez de Ocáriz Borde, Artem Lukoianov, Anastasis Kratsios, Michael M. Bronstein, Xiaowen Dong:
Scalable Message Passing Neural Networks: No Need for Attention in Large Graph Representation Learning. CoRR abs/2411.00835 (2024) - [i119]Benedict Aaron Tjandra, Federico Barbero, Michael M. Bronstein:
Enhancing the Expressivity of Temporal Graph Networks through Source-Target Identification. CoRR abs/2411.03596 (2024) - 2023
- [j67]Kamilia Zaripova, Luca Cosmo, Anees Kazi, Seyed-Ahmad Ahmadi, Michael M. Bronstein, Nassir Navab:
Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications. Medical Image Anal. 88: 102839 (2023) - [j66]Giorgos Bouritsas, Fabrizio Frasca, Stefanos Zafeiriou, Michael M. Bronstein:
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 657-668 (2023) - [j65]Anees Kazi, Luca Cosmo, Seyed-Ahmad Ahmadi, Nassir Navab, Michael M. Bronstein:
Differentiable Graph Module (DGM) for Graph Convolutional Networks. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 1606-1617 (2023) - [j64]Francesco Di Giovanni, James Rowbottom, Benjamin Paul Chamberlain, Thomas Markovich, Michael M. Bronstein:
Understanding convolution on graphs via energies. Trans. Mach. Learn. Res. 2023 (2023) - [c142]Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderón, Michael M. Bronstein, Marcello Restelli:
Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization. AAAI 2023: 9251-9259 - [c141]Edoardo Cetin, Benjamin Paul Chamberlain, Michael M. Bronstein, Jonathan J. Hunt:
Hyperbolic Deep Reinforcement Learning. ICLR 2023 - [c140]Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Yannick Hammerla, Michael M. Bronstein, Max Hansmire:
Graph Neural Networks for Link Prediction with Subgraph Sketching. ICLR 2023 - [c139]T. Konstantin Rusch, Benjamin Paul Chamberlain, Michael W. Mahoney, Michael M. Bronstein, Siddhartha Mishra:
Gradient Gating for Deep Multi-Rate Learning on Graphs. ICLR 2023 - [c138]Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio, Michael M. Bronstein:
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology. ICML 2023: 7865-7885 - [c137]Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni:
DRew: Dynamically Rewired Message Passing with Delay. ICML 2023: 12252-12267 - [c136]Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein:
Edge Directionality Improves Learning on Heterophilic Graphs. LoG 2023: 25 - [c135]Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany:
Temporal Graph Benchmark for Machine Learning on Temporal Graphs. NeurIPS 2023 - [c134]Joshua Southern, Jeremy Wayland, Michael M. Bronstein, Bastian Rieck:
Curvature Filtrations for Graph Generative Model Evaluation. NeurIPS 2023 - [c133]Floor Eijkelboom, Erik J. Bekkers, Michael M. Bronstein, Francesco Di Giovanni:
Can strong structural encoding reduce the importance of Message Passing? TAG-ML 2023: 278-288 - [i118]Joshua Southern, Jeremy Wayland, Michael M. Bronstein, Bastian Rieck:
Curvature Filtrations for Graph Generative Model Evaluation. CoRR abs/2301.12906 (2023) - [i117]Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio', Michael M. Bronstein:
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology. CoRR abs/2302.02941 (2023) - [i116]T. Konstantin Rusch, Michael M. Bronstein, Siddhartha Mishra:
A Survey on Oversmoothing in Graph Neural Networks. CoRR abs/2303.10993 (2023) - [i115]Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni:
DRew: Dynamically Rewired Message Passing with Delay. CoRR abs/2305.08018 (2023) - [i114]Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein:
Edge Directionality Improves Learning on Heterophilic Graphs. CoRR abs/2305.10498 (2023) - [i113]Claudio Battiloro, Indro Spinelli, Lev Telyatnikov, Michael M. Bronstein, Simone Scardapane, Paolo Di Lorenzo:
From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module. CoRR abs/2305.16174 (2023) - [i112]Francesco Di Giovanni, T. Konstantin Rusch, Michael M. Bronstein, Andreea Deac, Marc Lackenby, Siddhartha Mishra, Petar Velickovic:
How does over-squashing affect the power of GNNs? CoRR abs/2306.03589 (2023) - [i111]Baskaran Sripathmanathan, Xiaowen Dong, Michael M. Bronstein:
On the Impact of Sample Size in Reconstructing Graph Signals. CoRR abs/2307.00336 (2023) - [i110]Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany:
Temporal Graph Benchmark for Machine Learning on Temporal Graphs. CoRR abs/2307.01026 (2023) - [i109]António Leitão, Maxime Lucas, Simone Poetto, Taylor A. Hersh, Shane Gero, David F. Gruber, Michael M. Bronstein, Giovanni Petri:
Social learning across symbolic cultural barriers in non-human cultures. CoRR abs/2307.05304 (2023) - [i108]Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji:
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR abs/2307.08423 (2023) - [i107]Ilia Igashov, Arne Schneuing, Marwin H. S. Segler, Michael M. Bronstein, Bruno E. Correia:
RetroBridge: Modeling Retrosynthesis with Markov Bridges. CoRR abs/2308.16212 (2023) - [i106]Jianan Zhao, Le Zhuo, Yikang Shen, Meng Qu, Kai Liu, Michael M. Bronstein, Zhaocheng Zhu, Jian Tang:
GraphText: Graph Reasoning in Text Space. CoRR abs/2310.01089 (2023) - [i105]Ben Finkelshtein, Xingyue Huang, Michael M. Bronstein, Ismail Ilkan Ceylan:
Cooperative Graph Neural Networks. CoRR abs/2310.01267 (2023) - [i104]Federico Barbero, Ameya Velingker, Amin Saberi, Michael M. Bronstein, Francesco Di Giovanni:
Locality-Aware Graph-Rewiring in GNNs. CoRR abs/2310.01668 (2023) - [i103]Avishek Joey Bose, Tara Akhound-Sadegh, Kilian Fatras, Guillaume Huguet, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael M. Bronstein, Alexander Tong:
SE(3)-Stochastic Flow Matching for Protein Backbone Generation. CoRR abs/2310.02391 (2023) - [i102]Qitian Wu, Chenxiao Yang, Kaipeng Zeng, Fan Nie, Michael M. Bronstein, Junchi Yan:
Advective Diffusion Transformers for Topological Generalization in Graph Learning. CoRR abs/2310.06417 (2023) - [i101]Floor Eijkelboom, Erik J. Bekkers, Michael M. Bronstein, Francesco Di Giovanni:
Can strong structural encoding reduce the importance of Message Passing? CoRR abs/2310.15197 (2023) - [i100]Alexandre Duval, Simon V. Mathis, Chaitanya K. Joshi, Victor Schmidt, Santiago Miret, Fragkiskos D. Malliaros, Taco Cohen, Pietro Lio, Yoshua Bengio, Michael M. Bronstein:
A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems. CoRR abs/2312.07511 (2023) - 2022
- [j63]Soha Sadat Mahdi, Harold S. Matthews, Nele Nauwelaers, Michiel Vanneste, Shunwang Gong, Giorgos Bouritsas, Gareth S. Baynam, Peter Hammond, Richard A. Spritz, Ophir D. Klein, Benedikt Hallgrímsson, Hilde Peeters, Michael M. Bronstein, Peter Claes:
Multi-Scale Part-Based Syndrome Classification of 3D Facial Images. IEEE Access 10: 23450-23462 (2022) - [j62]Luca Cosmo, Giorgia Minello, Michael M. Bronstein, Emanuele Rodolà, Luca Rossi, Andrea Torsello:
3D Shape Analysis Through a Quantum Lens: the Average Mixing Kernel Signature. Int. J. Comput. Vis. 130(6): 1474-1493 (2022) - [j61]Stefanos Zafeiriou, Michael M. Bronstein, Taco Cohen, Oriol Vinyals, Le Song, Jure Leskovec, Pietro Liò, Joan Bruna, Marco Gori:
Guest Editorial: Non-Euclidean Machine Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44(2): 723-726 (2022) - [j60]Soha Sadat Mahdi, Nele Nauwelaers, Philip Joris, Giorgos Bouritsas, Shunwang Gong, Susan Walsh, Mark D. Shriver, Michael M. Bronstein, Peter Claes:
Matching 3D Facial Shape to Demographic Properties by Geometric Metric Learning: A Part-Based Approach. IEEE Trans. Biom. Behav. Identity Sci. 4(2): 163-172 (2022) - [c132]Emanuele Rodolà, Luca Cosmo, Maks Ovsjanikov, Arianna Rampini, Simone Melzi, Michael M. Bronstein, Riccardo Marin:
Inverse Computational Spectral Geometry. Eurographics (Tutorials) 2022 - [c131]Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron:
Equivariant Subgraph Aggregation Networks. ICLR 2022 - [c130]Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein:
Understanding over-squashing and bottlenecks on graphs via curvature. ICLR 2022 - [c129]Emanuele Rossi, Federico Monti, Yan Leng, Michael M. Bronstein, Xiaowen Dong:
Learning to Infer Structures of Network Games. ICML 2022: 18809-18827 - [c128]T. Konstantin Rusch, Ben Chamberlain, James Rowbottom, Siddhartha Mishra, Michael M. Bronstein:
Graph-Coupled Oscillator Networks. ICML 2022: 18888-18909 - [c127]Michael M. Bronstein:
Neural Diffusion PDEs, Differential Geometry, and Graph Neural Networks. IMPROVE 2022: 7 - [c126]Ahmed El-Kishky, Michael M. Bronstein, Ying Xiao, Aria Haghighi:
Graph-based Representation Learning for Web-scale Recommender Systems. KDD 2022: 4784-4785 - [c125]Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein:
On the Unreasonable Effectiveness of Feature Propagation in Learning on Graphs With Missing Node Features. LoG 2022: 11 - [c124]Cristian Bodnar, Francesco Di Giovanni, Benjamin Paul Chamberlain, Pietro Lió, Michael M. Bronstein:
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs. NeurIPS 2022 - [c123]Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron:
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries. NeurIPS 2022 - [c122]Federico Barbero, Cristian Bodnar, Haitz Sáez de Ocáriz Borde, Michael M. Bronstein, Petar Velickovic, Pietro Liò:
Sheaf Neural Networks with Connection Laplacians. TAG-ML 2022: 28-36 - [e9]Luigi Manfredi, Seyed-Ahmad Ahmadi, Michael M. Bronstein, Anees Kazi, Davide Lomanto, Alwyn Mathew, Ludovic Magerand, Kamilia Mullakaeva, Bartlomiej W. Papiez, Russell H. Taylor, Emanuele Trucco:
Imaging Systems for GI Endoscopy, and Graphs in Biomedical Image Analysis - First MICCAI Workshop, ISGIE 2022, and Fourth MICCAI Workshop, GRAIL 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings. Lecture Notes in Computer Science 13754, Springer 2022, ISBN 978-3-031-21082-2 [contents] - [i99]Francesco Di Giovanni, Giulia Luise, Michael M. Bronstein:
Heterogeneous manifolds for curvature-aware graph embedding. CoRR abs/2202.01185 (2022) - [i98]T. Konstantin Rusch, Benjamin Paul Chamberlain, James Rowbottom, Siddhartha Mishra, Michael M. Bronstein:
Graph-Coupled Oscillator Networks. CoRR abs/2202.02296 (2022) - [i97]Paul Bertin, Jarrid Rector-Brooks, Deepak Sharma, Thomas Gaudelet, Andrew Anighoro, Torsten Gross, Francisco Martinez-Pena, Eileen L. Tang, Suraj M. S, Cristian Regep, Jeremy B. R. Hayter, Maksym Korablyov, Nicholas Valiante, Almer van der Sloot, Mike Tyers, Charles Roberts, Michael M. Bronstein, Luke L. Lairson, Jake P. Taylor-King, Yoshua Bengio:
RECOVER: sequential model optimization platform for combination drug repurposing identifies novel synergistic compounds in vitro. CoRR abs/2202.04202 (2022) - [i96]Cristian Bodnar, Francesco Di Giovanni, Benjamin Paul Chamberlain, Pietro Liò, Michael M. Bronstein:
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs. CoRR abs/2202.04579 (2022) - [i95]Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderón, Michael M. Bronstein, Marcello Restelli:
Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization. CoRR abs/2202.06545 (2022) - [i94]Kamilia Mullakaeva, Luca Cosmo, Anees Kazi, Seyed-Ahmad Ahmadi, Nassir Navab, Michael M. Bronstein:
Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications. CoRR abs/2204.00323 (2022) - [i93]Ahmed A. A. Elhag, Gabriele Corso, Hannes Stärk, Michael M. Bronstein:
Graph Anisotropic Diffusion. CoRR abs/2205.00354 (2022) - [i92]Emanuele Rossi, Federico Monti, Yan Leng, Michael M. Bronstein, Xiaowen Dong:
Learning to Infer Structures of Network Games. CoRR abs/2206.08119 (2022) - [i91]Federico Barbero, Cristian Bodnar, Haitz Sáez de Ocáriz Borde, Michael M. Bronstein, Petar Velickovic, Pietro Liò:
Sheaf Neural Networks with Connection Laplacians. CoRR abs/2206.08702 (2022) - [i90]Francesco Di Giovanni, James Rowbottom, Benjamin Paul Chamberlain, Thomas Markovich, Michael M. Bronstein:
Graph Neural Networks as Gradient Flows. CoRR abs/2206.10991 (2022) - [i89]Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron:
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries. CoRR abs/2206.11140 (2022) - [i88]Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Hammerla, Michael M. Bronstein, Max Hansmire:
Graph Neural Networks for Link Prediction with Subgraph Sketching. CoRR abs/2209.15486 (2022) - [i87]T. Konstantin Rusch, Benjamin Paul Chamberlain, Michael W. Mahoney, Michael M. Bronstein, Siddhartha Mishra:
Gradient Gating for Deep Multi-Rate Learning on Graphs. CoRR abs/2210.00513 (2022) - [i86]Edoardo Cetin, Benjamin Paul Chamberlain, Michael M. Bronstein, Jonathan J. Hunt:
Hyperbolic Deep Reinforcement Learning. CoRR abs/2210.01542 (2022) - [i85]Ilia Igashov, Hannes Stärk, Clément Vignac, Victor Garcia Satorras, Pascal Frossard, Max Welling, Michael M. Bronstein, Bruno E. Correia:
Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design. CoRR abs/2210.05274 (2022) - [i84]Arne Schneuing, Yuanqi Du, Charles Harris, Arian R. Jamasb, Ilia Igashov, Weitao Du, Tom L. Blundell, Pietro Lió, Carla Gomes, Max Welling, Michael M. Bronstein, Bruno E. Correia:
Structure-based Drug Design with Equivariant Diffusion Models. CoRR abs/2210.13695 (2022) - 2021
- [j59]Thomas Gaudelet, Ben Day, Arian R. Jamasb, Jyothish Soman, Cristian Regep, Gertrude Liu, Jeremy B. R. Hayter, Richard Vickers, Charles Roberts, Jian Tang, David Roblin, Tom L. Blundell, Michael M. Bronstein, Jake P. Taylor-King:
Utilizing graph machine learning within drug discovery and development. Briefings Bioinform. 22(6) (2021) - [j58]Filippo Maggioli, Simone Melzi, Maksim Ovsjanikov, Michael M. Bronstein, Emanuele Rodolà:
Orthogonalized Fourier Polynomials for Signal Approximation and Transfer. Comput. Graph. Forum 40(2): 435-447 (2021) - [j57]Mehdi Bahri, Eimear O' Sullivan, Shunwang Gong, Feng Liu, Xiaoming Liu, Michael M. Bronstein, Stefanos Zafeiriou:
Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation. Int. J. Comput. Vis. 129(9): 2680-2713 (2021) - [j56]Ron Levie, Wei Huang, Lorenzo Bucci, Michael M. Bronstein, Gitta Kutyniok:
Transferability of Spectral Graph Convolutional Neural Networks. J. Mach. Learn. Res. 22: 272:1-272:59 (2021) - [j55]Stefan C. Schonsheck, Michael M. Bronstein, Rongjie Lai:
Nonisometric Surface Registration via Conformal Laplace-Beltrami Basis Pursuit. J. Sci. Comput. 86(3): 30 (2021) - [c121]Freyr Sverrisson, Jean Feydy, Bruno E. Correia, Michael M. Bronstein:
Fast End-to-End Learning on Protein Surfaces. CVPR 2021: 15272-15281 - [c120]Cristian Bodnar, Fabrizio Frasca, Yuguang Wang, Nina Otter, Guido F. Montúfar, Pietro Lió, Michael M. Bronstein:
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks. ICML 2021: 1026-1037 - [c119]Ben Chamberlain, James Rowbottom, Maria I. Gorinova, Michael M. Bronstein, Stefan Webb, Emanuele Rossi:
GRAND: Graph Neural Diffusion. ICML 2021: 1407-1418 - [c118]Balder Croquet, Daan Christiaens, Seth M. Weinberg, Michael M. Bronstein, Dirk Vandermeulen, Peter Claes:
Unsupervised Diffeomorphic Surface Registration and Non-linear Modelling. MICCAI (4) 2021: 118-128 - [c117]Ben Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael M. Bronstein:
Beltrami Flow and Neural Diffusion on Graphs. NeurIPS 2021: 1594-1609 - [c116]Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yuguang Wang, Pietro Liò, Guido F. Montúfar, Michael M. Bronstein:
Weisfeiler and Lehman Go Cellular: CW Networks. NeurIPS 2021: 2625-2640 - [c115]Giorgos Bouritsas, Andreas Loukas, Nikolaos Karalias, Michael M. Bronstein:
Partition and Code: learning how to compress graphs. NeurIPS 2021: 18603-18619 - [c114]Luca Belli, Alykhan Tejani, Frank Portman, Alexandre Lung-Yut-Fong, Ben Chamberlain, Yuanpu Xie, Kristian Lum, Jonathan Hunt, Michael M. Bronstein, Vito Walter Anelli, Saikishore Kalloori, Bruce Ferwerda, Wenzhe Shi:
The 2021 RecSys Challenge Dataset: Fairness is not optional. RecSys Challenge 2021: 1-6 - [c113]Thibaut Thonet, Stéphane Clinchant, Carlos Lassance, Elvin Isufi, Jiaqi Ma, Yutong Xie, Jean-Michel Renders, Michael M. Bronstein:
GReS: Workshop on Graph Neural Networks for Recommendation and Search. RecSys 2021: 780-782 - [c112]Vito Walter Anelli, Saikishore Kalloori, Bruce Ferwerda, Luca Belli, Alykhan Tejani, Frank Portman, Alexandre Lung-Yut-Fong, Ben Chamberlain, Yuanpu Xie, Jonathan Hunt, Michael M. Bronstein, Wenzhe Shi:
RecSys 2021 Challenge Workshop: Fairness-aware engagement prediction at scale on Twitter's Home Timeline. RecSys 2021: 819-824 - [i83]Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido Montúfar, Pietro Liò, Michael M. Bronstein:
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks. CoRR abs/2103.03212 (2021) - [i82]Jacob Andreas, Gasper Begus, Michael M. Bronstein, Roee Diamant, Denley Delaney, Shane Gero, Shafi Goldwasser, David F. Gruber, Sarah de Haas, Peter Malkin, Roger Payne, Giovanni Petri, Daniela Rus, Pratyusha Sharma, Dan Tchernov, Pernille Tønnesen, Antonio Torralba, Daniel M. Vogt, Robert J. Wood:
Cetacean Translation Initiative: a roadmap to deciphering the communication of sperm whales. CoRR abs/2104.08614 (2021) - [i81]Michael M. Bronstein, Joan Bruna, Taco Cohen, Petar Velickovic:
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges. CoRR abs/2104.13478 (2021) - [i80]Benjamin Paul Chamberlain, James Rowbottom, Maria I. Gorinova, Stefan Webb, Emanuele Rossi, Michael M. Bronstein:
GRAND: Graph Neural Diffusion. CoRR abs/2106.10934 (2021) - [i79]Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yu Guang Wang, Pietro Liò, Guido Montúfar, Michael M. Bronstein:
Weisfeiler and Lehman Go Cellular: CW Networks. CoRR abs/2106.12575 (2021) - [i78]Giorgos Bouritsas, Andreas Loukas, Nikolaos Karalias, Michael M. Bronstein:
Partition and Code: learning how to compress graphs. CoRR abs/2107.01952 (2021) - [i77]Luca Belli, Alykhan Tejani, Frank Portman, Alexandre Lung-Yut-Fong, Ben Chamberlain, Yuanpu Xie, Kristian Lum, Jonathan Hunt, Michael M. Bronstein, Vito Walter Anelli, Saikishore Kalloori, Bruce Ferwerda, Wenzhe Shi:
The 2021 RecSys Challenge Dataset: Fairness is not optional. CoRR abs/2109.08245 (2021) - [i76]Balder Croquet, Daan Christiaens, Seth M. Weinberg, Michael M. Bronstein, Dirk Vandermeulen, Peter Claes:
Unsupervised Diffeomorphic Surface Registration and Non-Linear Modelling. CoRR abs/2109.13630 (2021) - [i75]Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron:
Equivariant Subgraph Aggregation Networks. CoRR abs/2110.02910 (2021) - [i74]Benjamin Paul Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael M. Bronstein:
Beltrami Flow and Neural Diffusion on Graphs. CoRR abs/2110.09443 (2021) - [i73]Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein:
On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features. CoRR abs/2111.12128 (2021) - [i72]Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein:
Understanding over-squashing and bottlenecks on graphs via curvature. CoRR abs/2111.14522 (2021) - [i71]Luca Cosmo, Giorgia Minello, Michael M. Bronstein, Emanuele Rodolà, Luca Rossi, Andrea Torsello:
Graph Kernel Neural Networks. CoRR abs/2112.07436 (2021) - 2020
- [j54]Aviad Zabatani, Vitaly Surazhsky, Erez Sperling, Sagi Ben-Moshe, Ohad Menashe, David H. Silver, Zachi Karni, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Intel® RealSense™ SR300 Coded Light Depth Camera. IEEE Trans. Pattern Anal. Mach. Intell. 42(10): 2333-2345 (2020) - [j53]Xiaowen Dong, Dorina Thanou, Laura Toni, Michael M. Bronstein, Pascal Frossard:
Graph Signal Processing for Machine Learning: A Review and New Perspectives. IEEE Signal Process. Mag. 37(6): 117-127 (2020) - [c111]Dominik Kulon, Riza Alp Güler, Iasonas Kokkinos, Michael M. Bronstein, Stefanos Zafeiriou:
Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild. CVPR 2020: 4989-4999 - [c110]Shunwang Gong, Mehdi Bahri, Michael M. Bronstein, Stefanos Zafeiriou:
Geometrically Principled Connections in Graph Neural Networks. CVPR 2020: 11412-11421 - [c109]Luca Cosmo, Giorgia Minello, Michael M. Bronstein, Luca Rossi, Andrea Torsello:
The Average Mixing Kernel Signature. ECCV (20) 2020: 1-17 - [c108]Jan Svoboda, Pietro Astolfi, Davide Boscaini, Jonathan Masci, Michael M. Bronstein:
Clustered Dynamic Graph CNN for Biometric 3D Hand Shape Recognition. IJCB 2020: 1-9 - [c107]Soha Sadat Mahdi, Nele Nauwelaers, Philip Joris, Giorgos Bouritsas, Shunwang Gong, Sergiy Bokhnyak, Susan Walsh, Mark D. Shriver, Michael M. Bronstein, Peter Claes:
3D Facial Matching by Spiral Convolutional Metric Learning and a Biometric Fusion-Net of Demographic Properties. ICPR 2020: 1757-1764 - [c106]Luca Cosmo, Anees Kazi, Seyed-Ahmad Ahmadi, Nassir Navab, Michael M. Bronstein:
Latent-Graph Learning for Disease Prediction. MICCAI (2) 2020: 643-653 - [c105]Jean Feydy, Joan Alexis Glaunès, Benjamin Charlier, Michael M. Bronstein:
Fast geometric learning with symbolic matrices. NeurIPS 2020 - [c104]Vito Walter Anelli, Amra Delic, Gabriele Sottocornola, Jessie Smith, Nazareno Andrade, Luca Belli, Michael M. Bronstein, Akshay Gupta, Sofia Ira Ktena, Alexandre Lung-Yut-Fong, Frank Portman, Alykhan Tejani, Yuanpu Xie, Xiao Zhu, Wenzhe Shi:
RecSys 2020 Challenge Workshop: Engagement Prediction on Twitter's Home Timeline. RecSys 2020: 623-627 - [c103]Benjamin Paul Chamberlain, Emanuele Rossi, Dan Shiebler, Suvash Sedhain, Michael M. Bronstein:
Tuning Word2vec for Large Scale Recommendation Systems. RecSys 2020: 732-737 - [i70]Guadalupe Gonzalez, Shunwang Gong, Ivan Laponogov, Kirill A. Veselkov, Michael M. Bronstein:
Graph Attentional Autoencoder for Anticancer Hyperfood Prediction. CoRR abs/2001.05724 (2020) - [i69]Anees Kazi, Luca Cosmo, Nassir Navab, Michael M. Bronstein:
Differentiable Graph Module (DGM) Graph Convolutional Networks. CoRR abs/2002.04999 (2020) - [i68]David Pickup, Xianfang Sun, Paul L. Rosin, Ralph R. Martin, Z. Cheng, Zhouhui Lian, Masaki Aono, A. Ben Hamza, Alexander M. Bronstein, Michael M. Bronstein, S. Bu, Umberto Castellani, S. Cheng, Valeria Garro, Andrea Giachetti, Afzal Godil, Luca Isaia, J. Han, Henry Johan, Long Lai, Bo Li, Chunyuan Li, Haisheng Li, Roee Litman, X. Liu, Z. Liu, Yijuan Lu, Li Sun, Gary K. L. Tam, Atsushi Tatsuma, Jianbo Ye:
Shape retrieval of non-rigid 3d human models. CoRR abs/2003.08763 (2020) - [i67]Luca Cosmo, Anees Kazi, Seyed-Ahmad Ahmadi, Nassir Navab, Michael M. Bronstein:
Latent Patient Network Learning for Automatic Diagnosis. CoRR abs/2003.13620 (2020) - [i66]Dominik Kulon, Riza Alp Güler, Iasonas Kokkinos, Michael M. Bronstein, Stefanos Zafeiriou:
Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild. CoRR abs/2004.01946 (2020) - [i65]Shunwang Gong, Mehdi Bahri, Michael M. Bronstein, Stefanos Zafeiriou:
Geometrically Principled Connections in Graph Neural Networks. CoRR abs/2004.02658 (2020) - [i64]Emanuele Rossi, Fabrizio Frasca, Ben Chamberlain, Davide Eynard, Michael M. Bronstein, Federico Monti:
SIGN: Scalable Inception Graph Neural Networks. CoRR abs/2004.11198 (2020) - [i63]Luca Belli, Sofia Ira Ktena, Alykhan Tejani, Alexandre Lung-Yut-Fong, Frank Portman, Xiao Zhu, Yuanpu Xie, Akshay Gupta, Michael M. Bronstein, Amra Delic, Gabriele Sottocornola, Vito Walter Anelli, Nazareno Andrade, Jessie Smith, Wenzhe Shi:
Privacy-Preserving Recommender Systems Challenge on Twitter's Home Timeline. CoRR abs/2004.13715 (2020) - [i62]Giorgos Bouritsas, Fabrizio Frasca, Stefanos Zafeiriou, Michael M. Bronstein:
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting. CoRR abs/2006.09252 (2020) - [i61]Emanuele Rossi, Ben Chamberlain, Fabrizio Frasca, Davide Eynard, Federico Monti, Michael M. Bronstein:
Temporal Graph Networks for Deep Learning on Dynamic Graphs. CoRR abs/2006.10637 (2020) - [i60]Xiaowen Dong, Dorina Thanou, Laura Toni, Michael M. Bronstein, Pascal Frossard:
Graph signal processing for machine learning: A review and new perspectives. CoRR abs/2007.16061 (2020) - [i59]Soha Sadat Mahdi, Nele Nauwelaers, Philip Joris, Giorgos Bouritsas, Shunwang Gong, Sergiy Bokhnyak, Susan Walsh, Mark D. Shriver, Michael M. Bronstein, Peter Claes:
3D Facial Matching by Spiral Convolutional Metric Learning and a Biometric Fusion-Net of Demographic Properties. CoRR abs/2009.04746 (2020) - [i58]Benjamin Paul Chamberlain, Emanuele Rossi, Dan Shiebler, Suvash Sedhain, Michael M. Bronstein:
Tuning Word2vec for Large Scale Recommendation Systems. CoRR abs/2009.12192 (2020) - [i57]Or Litany, Emanuele Rodolà, Alex M. Bronstein, Michael M. Bronstein, Daniel Cremers:
Non-Rigid Puzzles. CoRR abs/2011.13076 (2020) - [i56]Thomas Gaudelet, Ben Day, Arian R. Jamasb, Jyothish Soman, Cristian Regep, Gertrude Liu, Jeremy B. R. Hayter, Richard Vickers, Charles Roberts, Jian Tang, David Roblin, Tom L. Blundell, Michael M. Bronstein, Jake P. Taylor-King:
Utilising Graph Machine Learning within Drug Discovery and Development. CoRR abs/2012.05716 (2020) - [i55]Mehdi Bahri, Eimear O' Sullivan, Shunwang Gong, Feng Liu, Xiaoming Liu, Michael M. Bronstein, Stefanos Zafeiriou:
Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation. CoRR abs/2012.09235 (2020)
2010 – 2019
- 2019
- [j52]Emanuele Rodolà, Zorah Lähner, Alexander M. Bronstein, Michael M. Bronstein, Justin Solomon:
Functional Maps Representation On Product Manifolds. Comput. Graph. Forum 38(1): 678-689 (2019) - [j51]Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E. Sarma, Michael M. Bronstein, Justin M. Solomon:
Dynamic Graph CNN for Learning on Point Clouds. ACM Trans. Graph. 38(5): 146:1-146:12 (2019) - [j50]Ron Levie, Federico Monti, Xavier Bresson, Michael M. Bronstein:
CayleyNets: Graph Convolutional Neural Networks With Complex Rational Spectral Filters. IEEE Trans. Signal Process. 67(1): 97-109 (2019) - [c102]Roberto M. Dyke, C. Stride, Yu-Kun Lai, Paul L. Rosin, Mathieu Aubry, Amit Boyarski, Alexander M. Bronstein, Michael M. Bronstein, Daniel Cremers, Matthew Fisher, Thibault Groueix, Daoliang Guo, Vladimir G. Kim, Ron Kimmel, Zorah Lähner, Kun Li, Or Litany, Tal Remez, Emanuele Rodolà, Bryan C. Russell, Yusuf Sahillioglu, Ron Slossberg, Gary K. L. Tam, Matthias Vestner, Z. Wu, Jingyu Yang:
Shape Correspondence with Isometric and Non-Isometric Deformations. 3DOR@Eurographics 2019: 111-119 - [c101]Dominik Kulon, Haoyang Wang, Riza Alp Güler, Michael M. Bronstein, Stefanos Zafeiriou:
Single Image 3D Hand Reconstruction with Mesh Convolutions. BMVC 2019: 45 - [c100]Simone Melzi, Riccardo Spezialetti, Federico Tombari, Michael M. Bronstein, Luigi Di Stefano, Emanuele Rodolà:
GFrames: Gradient-Based Local Reference Frame for 3D Shape Matching. CVPR 2019: 4629-4638 - [c99]Luca Cosmo, Mikhail Panine, Arianna Rampini, Maks Ovsjanikov, Michael M. Bronstein, Emanuele Rodolà:
Isospectralization, or How to Hear Shape, Style, and Correspondence. CVPR 2019: 7529-7538 - [c98]Michael M. Bronstein, Leonidas J. Guibas, Iasonas Kokkinos, Or Litany, Niloy J. Mitra, Federico Monti, Emanuele Rodolà:
Deep Learning for Computer Graphics and Geometry Processing. Eurographics (Tutorials) 2019: 43 - [c97]Giorgos Bouritsas, Sergiy Bokhnyak, Stylianos Ploumpis, Stefanos Zafeiriou, Michael M. Bronstein:
Neural 3D Morphable Models: Spiral Convolutional Networks for 3D Shape Representation Learning and Generation. ICCV 2019: 7212-7221 - [c96]Shunwang Gong, Lei Chen, Michael M. Bronstein, Stefanos Zafeiriou:
SpiralNet++: A Fast and Highly Efficient Mesh Convolution Operator. ICCV Workshops 2019: 4141-4148 - [c95]Jan Svoboda, Jonathan Masci, Federico Monti, Michael M. Bronstein, Leonidas J. Guibas:
PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks. ICLR (Poster) 2019 - [i54]Federico Monti, Fabrizio Frasca, Davide Eynard, Damon Mannion, Michael M. Bronstein:
Fake News Detection on Social Media using Geometric Deep Learning. CoRR abs/1902.06673 (2019) - [i53]Shiyang Cheng, Michael M. Bronstein, Yuxiang Zhou, Irene Kotsia, Maja Pantic, Stefanos Zafeiriou:
MeshGAN: Non-linear 3D Morphable Models of Faces. CoRR abs/1903.10384 (2019) - [i52]Dominik Kulon, Haoyang Wang, Riza Alp Güler, Michael M. Bronstein, Stefanos Zafeiriou:
Single Image 3D Hand Reconstruction with Mesh Convolutions. CoRR abs/1905.01326 (2019) - [i51]Giorgos Bouritsas, Sergiy Bokhnyak, Stylianos Ploumpis, Michael M. Bronstein, Stefanos Zafeiriou:
Neural 3D Morphable Models: Spiral Convolutional Networks for 3D Shape Representation Learning and Generation. CoRR abs/1905.02876 (2019) - [i50]Emanuele Rossi, Federico Monti, Michael M. Bronstein, Pietro Liò:
ncRNA Classification with Graph Convolutional Networks. CoRR abs/1905.06515 (2019) - [i49]Ron Levie, Michael M. Bronstein, Gitta Kutyniok:
Transferability of Spectral Graph Convolutional Neural Networks. CoRR abs/1907.12972 (2019) - [i48]Fabrizio Frasca, Diego Galeano, Guadalupe Gonzalez, Ivan Laponogov, Kirill A. Veselkov, Alberto Paccanaro, Michael M. Bronstein:
Learning interpretable disease self-representations for drug repositioning. CoRR abs/1909.06609 (2019) - [i47]Shunwang Gong, Lei Chen, Michael M. Bronstein, Stefanos Zafeiriou:
SpiralNet++: A Fast and Highly Efficient Mesh Convolution Operator. CoRR abs/1911.05856 (2019) - 2018
- [j49]Dorian Nogneng, Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael M. Bronstein, Maks Ovsjanikov:
Improved Functional Mappings via Product Preservation. Comput. Graph. Forum 37(2): 179-190 (2018) - [j48]Anne Gehre, Michael M. Bronstein, Leif Kobbelt, Justin Solomon:
Interactive Curve Constrained Functional Maps. Comput. Graph. Forum 37(5): 1-12 (2018) - [j47]Larry Wang, Anne Gehre, Michael M. Bronstein, Justin Solomon:
Kernel Functional Maps. Comput. Graph. Forum 37(5): 27-36 (2018) - [j46]Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael M. Bronstein:
Localized Manifold Harmonics for Spectral Shape Analysis. Comput. Graph. Forum 37(6): 20-34 (2018) - [c94]Or Litany, Alexander M. Bronstein, Michael M. Bronstein, Ameesh Makadia:
Deformable Shape Completion With Graph Convolutional Autoencoders. CVPR 2018: 1886-1895 - [c93]Federico Monti, Karl Otness, Michael M. Bronstein:
MOTIFNET: A Motif-Based Graph Convolutional Network for Directed Graphs. DSW 2018: 225-228 - [c92]Federico Monti, Michael M. Bronstein, Xavier Bresson:
Deep Geometric Matrix Completion: A New Way for Recommender Systems. ICASSP 2018: 6852-6856 - [c91]Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer R. Klein, Joan Bruna:
Graph Neural Networks for IceCube Signal Classification. ICMLA 2018: 386-391 - [c90]Emanuele Rodolà, Zorah Lähner, Alex M. Bronstein, Michael M. Bronstein, Justin Solomon:
Functional Maps on Product Manifolds. SGP (Posters) 2018: 9-10 - [i46]Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E. Sarma, Michael M. Bronstein, Justin M. Solomon:
Dynamic Graph CNN for Learning on Point Clouds. CoRR abs/1801.07829 (2018) - [i45]Federico Monti, Karl Otness, Michael M. Bronstein:
MotifNet: a motif-based Graph Convolutional Network for directed graphs. CoRR abs/1802.01572 (2018) - [i44]Jan Svoboda, Jonathan Masci, Federico Monti, Michael M. Bronstein, Leonidas J. Guibas:
PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks. CoRR abs/1806.00088 (2018) - [i43]Federico Monti, Oleksandr Shchur, Aleksandar Bojchevski, Or Litany, Stephan Günnemann, Michael M. Bronstein:
Dual-Primal Graph Convolutional Networks. CoRR abs/1806.00770 (2018) - [i42]Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer R. Klein, Joan Bruna:
Graph Neural Networks for IceCube Signal Classification. CoRR abs/1809.06166 (2018) - [i41]Stefan C. Schonsheck, Michael M. Bronstein, Rongjie Lai:
Nonisometric Surface Registration via Conformal Laplace-Beltrami Basis Pursuit. CoRR abs/1809.07399 (2018) - [i40]Emanuele Rodolà, Zorah Lähner, Alexander M. Bronstein, Michael M. Bronstein, Justin Solomon:
Functional Maps Representation on Product Manifolds. CoRR abs/1809.10940 (2018) - [i39]Luca Cosmo, Mikhail Panine, Arianna Rampini, Maks Ovsjanikov, Michael M. Bronstein, Emanuele Rodolà:
Isospectralization, or how to hear shape, style, and correspondence. CoRR abs/1811.11465 (2018) - 2017
- [j45]Emanuele Rodolà, Luca Cosmo, Michael M. Bronstein, Andrea Torsello, Daniel Cremers:
Partial Functional Correspondence. Comput. Graph. Forum 36(1): 222-236 (2017) - [j44]Or Litany, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein:
Fully Spectral Partial Shape Matching. Comput. Graph. Forum 36(2): 247-258 (2017) - [j43]Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, Pierre Vandergheynst:
Geometric Deep Learning: Going beyond Euclidean data. IEEE Signal Process. Mag. 34(4): 18-42 (2017) - [c89]Andrea Gasparetto, Luca Cosmo, Emanuele Rodolà, Michael M. Bronstein, Andrea Torsello:
Spatial Maps: From Low Rank Spectral to Sparse Spatial Functional Representations. 3DV 2017: 477-485 - [c88]Matthias Vestner, Zorah Lähner, Amit Boyarski, Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Daniel Cremers:
Efficient Deformable Shape Correspondence via Kernel Matching. 3DV 2017: 517-526 - [c87]Emanuele Rodolà, Luca Cosmo, Or Litany, Michael M. Bronstein, Alexander M. Bronstein, Nicolas Audebert, A. Ben Hamza, Alexandre Boulch, Umberto Castellani, Minh N. Do, Duc Anh Duong, Takahiko Furuya, Andrea Gasparetto, Y. Hong, J. Kim, Bertrand Le Saux, Roee Litman, Majid Masoumi, Giorgia Minello, Hai-Dang Nguyen, V.-T. Nguyen, Ryutarou Ohbuchi, Viet-Khoi Pham, Thuyen V. Phan, M. Rezaei, Andrea Torsello, Minh-Triet Tran, Q. T. Tran, Bao Truong, L. Wan, Changqing Zou:
Deformable Shape Retrieval with Missing Parts. 3DOR@Eurographics 2017 - [c86]Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Jan Svoboda, Michael M. Bronstein:
Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs. CVPR 2017: 5425-5434 - [c85]Jan Svoboda, Federico Monti, Michael M. Bronstein:
Generative convolutional networks for latent fingerprint reconstruction. IJCB 2017: 429-436 - [c84]Or Litany, Tal Remez, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein:
Deep Functional Maps: Structured Prediction for Dense Shape Correspondence. ICCV 2017: 5660-5668 - [c83]Federico Monti, Michael M. Bronstein, Xavier Bresson:
Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks. NIPS 2017: 3697-3707 - [c82]Amit Boyarski, Alexander M. Bronstein, Michael M. Bronstein:
Subspace Least Squares Multidimensional Scaling. SSVM 2017: 681-693 - [c81]Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael M. Bronstein:
Localized Manifold Harmonics for Spectral Shape Analysis. SGP (Posters) 2017: 5-6 - [c80]Maks Ovsjanikov, Etienne Corman, Michael M. Bronstein, Emanuele Rodolà, Mirela Ben-Chen, Leonidas J. Guibas, Frédéric Chazal, Alexander M. Bronstein:
Computing and processing correspondences with functional maps. SIGGRAPH Courses 2017: 5:1-5:62 - [i38]Federico Monti, Michael M. Bronstein, Xavier Bresson:
Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks. CoRR abs/1704.06803 (2017) - [i37]Or Litany, Tal Remez, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein:
Deep Functional Maps: Structured Prediction for Dense Shape Correspondence. CoRR abs/1704.08686 (2017) - [i36]Jan Svoboda, Federico Monti, Michael M. Bronstein:
Generative Convolutional Networks for Latent Fingerprint Reconstruction. CoRR abs/1705.01707 (2017) - [i35]Ron Levie, Federico Monti, Xavier Bresson, Michael M. Bronstein:
CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters. CoRR abs/1705.07664 (2017) - [i34]Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael M. Bronstein:
Localized Manifold Harmonics for Spectral Shape Analysis. CoRR abs/1707.02596 (2017) - [i33]Zorah Lähner, Matthias Vestner, Amit Boyarski, Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Daniel Cremers:
Efficient Deformable Shape Correspondence via Kernel Matching. CoRR abs/1707.08991 (2017) - [i32]Amit Boyarski, Alexander M. Bronstein, Michael M. Bronstein:
Subspace Least Squares Multidimensional Scaling. CoRR abs/1709.03484 (2017) - [i31]Or Litany, Alexander M. Bronstein, Michael M. Bronstein, Ameesh Makadia:
Deformable Shape Completion with Graph Convolutional Autoencoders. CoRR abs/1712.00268 (2017) - 2016
- [j42]Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Michael M. Bronstein, Daniel Cremers:
Anisotropic Diffusion Descriptors. Comput. Graph. Forum 35(2): 431-441 (2016) - [j41]Or Litany, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein, Daniel Cremers:
Non-Rigid Puzzles. Comput. Graph. Forum 35(5): 135-143 (2016) - [j40]Silvia Biasotti, Andrea Cerri, Alexander M. Bronstein, Michael M. Bronstein:
Recent Trends, Applications, and Perspectives in 3D Shape Similarity Assessment. Comput. Graph. Forum 35(6): 87-119 (2016) - [j39]David Pickup, Xianfang Sun, Paul L. Rosin, Ralph R. Martin, Z. Cheng, Zhouhui Lian, Masaki Aono, A. Ben Hamza, Alexander M. Bronstein, Michael M. Bronstein, S. Bu, Umberto Castellani, S. Cheng, Valeria Garro, Andrea Giachetti, Afzal Godil, Luca Isaia, J. Han, Henry Johan, Long Lai, Bo Li, Chen-Feng Li, Haisheng Li, Roee Litman, X. Liu, Z. Liu, Yijuan Lu, Li Sun, Gary K. L. Tam, Atsushi Tatsuma, Jianbo Ye:
Shape Retrieval of Non-rigid 3D Human Models. Int. J. Comput. Vis. 120(2): 169-193 (2016) - [c79]Luca Cosmo, Emanuele Rodolà, Jonathan Masci, Andrea Torsello, Michael M. Bronstein:
Matching Deformable Objects in Clutter. 3DV 2016: 1-10 - [c78]Davide Eynard, Emanuele Rodolà, Klaus Glashoff, Michael M. Bronstein:
Coupled Functional Maps. 3DV 2016: 399-407 - [c77]Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael M. Bronstein:
Shape Analysis with Anisotropic Windowed Fourier Transform. 3DV 2016: 470-478 - [c76]Luca Cosmo, Emanuele Rodolà, Michael M. Bronstein, Andrea Torsello, Daniel Cremers, Yusuf Sahillioglu:
Partial Matching of Deformable Shapes. 3DOR@Eurographics 2016 - [c75]Zorah Lähner, Emanuele Rodolà, Michael M. Bronstein, Daniel Cremers, Oliver Burghard, Luca Cosmo, Alexander Dieckmann, Reinhard Klein, Yusuf Sahillioglu:
Matching of Deformable Shapes with Topological Noise. 3DOR@Eurographics 2016 - [c74]Zorah Lähner, Emanuele Rodolà, Frank R. Schmidt, Michael M. Bronstein, Daniel Cremers:
Efficient Globally Optimal 2D-to-3D Deformable Shape Matching. CVPR 2016: 2185-2193 - [c73]Artiom Kovnatsky, Klaus Glashoff, Michael M. Bronstein:
MADMM: A Generic Algorithm for Non-smooth Optimization on Manifolds. ECCV (5) 2016: 680-696 - [c72]Michael M. Bronstein, Evangelos Kalogerakis, Emanuele Rodolà, Jonathan Masci, Davide Boscaini:
Deep Learning for Shape Analysis. Eurographics (Tutorials) 2016 - [c71]Jan Svoboda, Jonathan Masci, Michael M. Bronstein:
Palmprint recognition via discriminative index learning. ICPR 2016: 4232-4237 - [c70]Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Michael M. Bronstein:
Learning shape correspondence with anisotropic convolutional neural networks. NIPS 2016: 3189-3197 - [c69]Jonathan Masci, Emanuele Rodolà, Davide Boscaini, Michael M. Bronstein, Hao Li:
Geometric deep learning. SIGGRAPH ASIA Courses 2016: 1:1-1:50 - [c68]Maks Ovsjanikov, Etienne Corman, Michael M. Bronstein, Emanuele Rodolà, Mirela Ben-Chen, Leonidas J. Guibas, Frédéric Chazal, Alexander M. Bronstein:
Computing and processing correspondences with functional maps. SIGGRAPH ASIA Courses 2016: 9:1-9:60 - [p5]Jonathan Pokrass, Alexander M. Bronstein, Michael M. Bronstein, Pablo Sprechmann, Guillermo Sapiro:
Sparse Models for Intrinsic Shape Correspondence. Perspectives in Shape Analysis 2016: 211-230 - [i30]Zorah Lähner, Emanuele Rodolà, Frank R. Schmidt, Michael M. Bronstein, Daniel Cremers:
Efficient Globally Optimal 2D-to-3D Deformable Shape Matching. CoRR abs/1601.06070 (2016) - [i29]Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Michael M. Bronstein:
Learning shape correspondence with anisotropic convolutional neural networks. CoRR abs/1605.06437 (2016) - [i28]Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, Pierre Vandergheynst:
Geometric deep learning: going beyond Euclidean data. CoRR abs/1611.08097 (2016) - [i27]Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Jan Svoboda, Michael M. Bronstein:
Geometric deep learning on graphs and manifolds using mixture model CNNs. CoRR abs/1611.08402 (2016) - 2015
- [j38]Davide Boscaini, Davide Eynard, Drosos Kourounis, Michael M. Bronstein:
Shape-from-Operator: Recovering Shapes from Intrinsic Operators. Comput. Graph. Forum 34(2): 265-274 (2015) - [j37]Davide Boscaini, Jonathan Masci, Simone Melzi, Michael M. Bronstein, Umberto Castellani, Pierre Vandergheynst:
Learning class-specific descriptors for deformable shapes using localized spectral convolutional networks. Comput. Graph. Forum 34(5): 13-23 (2015) - [j36]Davide Eynard, Artiom Kovnatsky, Michael M. Bronstein, Klaus Glashoff, Alexander M. Bronstein:
Multimodal Manifold Analysis by Simultaneous Diagonalization of Laplacians. IEEE Trans. Pattern Anal. Mach. Intell. 37(12): 2505-2517 (2015) - [c67]Artiom Kovnatsky, Michael M. Bronstein, Xavier Bresson, Pierre Vandergheynst:
Functional correspondence by matrix completion. CVPR 2015: 905-914 - [c66]Jan Svoboda, Michael M. Bronstein, Martin Drahanský:
Contactless biometric hand geometry recognition using a low-cost 3D camera. ICB 2015: 452-457 - [c65]Nauman Shahid, Vassilis Kalofolias, Xavier Bresson, Michael M. Bronstein, Pierre Vandergheynst:
Robust Principal Component Analysis on Graphs. ICCV 2015: 2812-2820 - [c64]Jonathan Masci, Davide Boscaini, Michael M. Bronstein, Pierre Vandergheynst:
Geodesic Convolutional Neural Networks on Riemannian Manifolds. ICCV Workshops 2015: 832-840 - [e8]Lourdes Agapito, Michael M. Bronstein, Carsten Rother:
Computer Vision - ECCV 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part I. Lecture Notes in Computer Science 8925, Springer 2015, ISBN 978-3-319-16177-8 [contents] - [e7]Lourdes Agapito, Michael M. Bronstein, Carsten Rother:
Computer Vision - ECCV 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part II. Lecture Notes in Computer Science 8926, Springer 2015, ISBN 978-3-319-16180-8 [contents] - [e6]Lourdes Agapito, Michael M. Bronstein, Carsten Rother:
Computer Vision - ECCV 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part III. Lecture Notes in Computer Science 8927, Springer 2015, ISBN 978-3-319-16198-3 [contents] - [e5]Lourdes Agapito, Michael M. Bronstein, Carsten Rother:
Computer Vision - ECCV 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part IV. Lecture Notes in Computer Science 8928, Springer 2015, ISBN 978-3-319-16219-5 [contents] - [e4]Matthias Teschner, Michael M. Bronstein:
36th Annual Conference of the European Association for Computer Graphics, Eurographics 2015 - Education Papers, Zurich, Switzerland, May 4-8, 2015. Eurographics Association 2015 [contents] - [r1]Alexander M. Bronstein, Michael M. Bronstein:
Manifold Intrinsic Similarity. Handbook of Mathematical Methods in Imaging 2015: 1859-1908 - [i26]Jonathan Masci, Davide Boscaini, Michael M. Bronstein, Pierre Vandergheynst:
ShapeNet: Convolutional Neural Networks on Non-Euclidean Manifolds. CoRR abs/1501.06297 (2015) - [i25]Nauman Shahid, Vassilis Kalofolias, Xavier Bresson, Michael M. Bronstein, Pierre Vandergheynst:
Robust Principal Component Analysis on Graphs. CoRR abs/1504.06151 (2015) - [i24]Artiom Kovnatsky, Klaus Glashoff, Michael M. Bronstein:
MADMM: a generic algorithm for non-smooth optimization on manifolds. CoRR abs/1505.07676 (2015) - [i23]Emanuele Rodolà, Luca Cosmo, Michael M. Bronstein, Andrea Torsello, Daniel Cremers:
Partial Functional Correspondence. CoRR abs/1506.05274 (2015) - 2014
- [j35]Davide Eynard, Artiom Kovnatsky, Michael M. Bronstein:
Laplacian colormaps: a framework for structure-preserving color transformations. Comput. Graph. Forum 33(2): 215-224 (2014) - [j34]Roee Litman, Alexander M. Bronstein, Michael M. Bronstein, Umberto Castellani:
Supervised learning of bag-of-features shape descriptors using sparse coding. Comput. Graph. Forum 33(5): 127-136 (2014) - [j33]Dan Raviv, Alexander M. Bronstein, Michael M. Bronstein, Dan Waisman, Nir A. Sochen, Ron Kimmel:
Equi-affine Invariant Geometry for Shape Analysis. J. Math. Imaging Vis. 50(1-2): 144-163 (2014) - [j32]Jonathan Masci, Michael M. Bronstein, Alexander M. Bronstein, Jürgen Schmidhuber:
Multimodal Similarity-Preserving Hashing. IEEE Trans. Pattern Anal. Mach. Intell. 36(4): 824-830 (2014) - [c63]Davide Boscaini, Ramunas Girdziusas, Michael M. Bronstein:
Coulomb Shapes: Using Electrostatic Forces for Deformation-invariant Shape Representation. 3DOR@Eurographics 2014: 9-15 - [c62]David Pickup, Xianfang Sun, Paul L. Rosin, Ralph R. Martin, Z. Cheng, Zhouhui Lian, Masaki Aono, Abdessamad Ben Hamza, Alexander M. Bronstein, Michael M. Bronstein, S. Bu, Umberto Castellani, S. Cheng, Valeria Garro, Andrea Giachetti, Afzal Godil, J. Han, Henry Johan, Long Lai, Bo Li, C. Li, Haisheng Li, Roee Litman, X. Liu, Z. Liu, Yijuan Lu, Atsushi Tatsuma, Jianbo Ye:
Shape Retrieval of Non-Rigid 3D Human Models. 3DOR@Eurographics 2014: 101-110 - [c61]Silvia Biasotti, Andrea Cerri, Alexander M. Bronstein, Michael M. Bronstein:
Quantifying 3D Shape Similarity Using Maps: Recent Trends, Applications and Perspectives. Eurographics (State of the Art Reports) 2014: 135-159 - [c60]Artiom Kovnatsky, Davide Eynard, Michael M. Bronstein:
Gamut mapping with image Laplacian commutators. ICIP 2014: 635-639 - [c59]Jonathan Masci, Alexander M. Bronstein, Michael M. Bronstein, Pablo Sprechmann, Guillermo Sapiro:
Sparse similarity-preserving hashing. ICLR 2014 - [p4]Jonathan Masci, Davide Migliore, Michael M. Bronstein, Jürgen Schmidhuber:
Descriptor Learning for Omnidirectional Image Matching. Registration and Recognition in Images and Videos 2014: 49-62 - [i22]Davide Boscaini, Davide Eynard, Michael M. Bronstein:
Shape-from-intrinsic operator. CoRR abs/1406.1925 (2014) - [i21]Vassilis Kalofolias, Xavier Bresson, Michael M. Bronstein, Pierre Vandergheynst:
Matrix Completion on Graphs. CoRR abs/1408.1717 (2014) - [i20]Artiom Kovnatsky, Michael M. Bronstein, Xavier Bresson, Pierre Vandergheynst:
Functional correspondence by matrix completion. CoRR abs/1412.8070 (2014) - 2013
- [j31]Artiom Kovnatsky, Michael M. Bronstein, Alexander M. Bronstein, Klaus Glashoff, Ron Kimmel:
Coupled quasi-harmonic bases. Comput. Graph. Forum 32(2): 439-448 (2013) - [j30]Jonathan Pokrass, Alexander M. Bronstein, Michael M. Bronstein, Pablo Sprechmann, Guillermo Sapiro:
Sparse Modeling of Intrinsic Correspondences. Comput. Graph. Forum 32(2): 459-468 (2013) - [c58]Pablo Sprechmann, Alexander M. Bronstein, Michael M. Bronstein, Guillermo Sapiro:
Learnable low rank sparse models for speech denoising. ICASSP 2013: 136-140 - [p3]Roee Litman, Alexander M. Bronstein, Michael M. Bronstein:
Stable Semi-local Features for Non-rigid Shapes. Innovations for Shape Analysis, Models and Algorithms 2013: 161-189 - [p2]Guy Rosman, Michael M. Bronstein, Alexander M. Bronstein, Alon Wolf, Ron Kimmel:
Group-Valued Regularization for Motion Segmentation of Articulated Shapes. Innovations for Shape Analysis, Models and Algorithms 2013: 263-281 - [e3]Michael M. Bronstein, Jean Favre, Kai Hormann:
18th International Workshop on Vision, Modeling, and Visualization, VMV 2013, Lugano, Switzerland, September 11-13, 2013. Eurographics Association 2013, ISBN 978-3-905674-51-4 [contents] - [i19]Klaus Glashoff, Michael M. Bronstein:
Almost-commuting matrices are almost jointly diagonalizable. CoRR abs/1305.2135 (2013) - [i18]Klaus Glashoff, Michael M. Bronstein:
Asymptotic metrics on the space of matrices under the commutation relation. CoRR abs/1305.2384 (2013) - [i17]Michael M. Bronstein, Klaus Glashoff, Terry A. Loring:
Making Laplacians commute. CoRR abs/1307.6549 (2013) - [i16]Davide Eynard, Artiom Kovnatsky, Michael M. Bronstein:
Structure-preserving color transformations using Laplacian commutativity. CoRR abs/1311.0119 (2013) - [i15]Michael M. Bronstein, Klaus Glashoff:
Heat kernel coupling for multiple graph analysis. CoRR abs/1312.3035 (2013) - 2012
- [j29]Roee Litman, Alexander M. Bronstein, Michael M. Bronstein:
Stable volumetric features in deformable shapes. Comput. Graph. 36(5): 569-576 (2012) - [j28]Stefano Marras, Michael M. Bronstein, Kai Hormann, Riccardo Scateni, Roberto Scopigno:
Motion-based mesh segmentation using augmented silhouettes. Graph. Model. 74(4): 164-172 (2012) - [j27]Christoph Strecha, Alexander M. Bronstein, Michael M. Bronstein, Pascal Fua:
LDAHash: Improved Matching with Smaller Descriptors. IEEE Trans. Pattern Anal. Mach. Intell. 34(1): 66-78 (2012) - [c57]Klaus Glashoff, Michael M. Bronstein:
Structure from Motion Using Augmented Lagrangian Robust Factorization. 3DIMPVT 2012: 379-386 - [c56]Artiom Kovnatsky, Michael M. Bronstein, Alexander M. Bronstein, Dan Raviv, Ron Kimmel:
Affine-Invariant Photometric Heat Kernel Signatures. 3DOR@Eurographics 2012: 39-46 - [c55]Guy Rosman, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Articulated Motion Segmentation of Point Clouds by Group-Valued Regularization. 3DOR@Eurographics 2012: 77-84 - [c54]Iasonas Kokkinos, Michael M. Bronstein, Roee Litman, Alexander M. Bronstein:
Intrinsic shape context descriptors for deformable shapes. CVPR 2012: 159-166 - [c53]Or Litany, Alexander M. Bronstein, Michael M. Bronstein:
Putting the Pieces Together: Regularized Multi-part Shape Matching. ECCV Workshops (1) 2012: 1-11 - [c52]Guy Rosman, Alexander M. Bronstein, Michael M. Bronstein, Xue-Cheng Tai, Ron Kimmel:
Group-Valued Regularization for Analysis of Articulated Motion. ECCV Workshops (1) 2012: 52-62 - [c51]Artiom Kovnatsky, Michael M. Bronstein, Alexander M. Bronstein:
Stable Spectral Mesh Filtering. ECCV Workshops (1) 2012: 83-91 - [c50]Michael M. Bronstein, Umberto Castellani, Alexander M. Bronstein:
Diffusion Geometry in Shape Analysis. Eurographics (Tutorials) 2012 - [p1]Alexander M. Bronstein, Michael M. Bronstein, Maks Ovsjanikov:
Feature-Based Methods in 3D Shape Analysis. 3D Imaging, Analysis and Applications 2012: 185-219 - [e2]Michela Spagnuolo, Michael M. Bronstein, Alexander M. Bronstein, Alfredo Ferreira:
5th Eurographics Workshop on 3D Object Retrieval, 3DOR@Eurographics 2012, Cagliari, Sardinia, Italy, May 13, 2012. Eurographics Association 2012, ISBN 978-3-905674-36-1 [contents] - [e1]Alfred M. Bruckstein, Bart M. ter Haar Romeny, Alexander M. Bronstein, Michael M. Bronstein:
Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Ein-Gedi, Israel, May 29 - June 2, 2011, Revised Selected Papers. Lecture Notes in Computer Science 6667, Springer 2012, ISBN 978-3-642-24784-2 [contents] - [i14]Jonathan Masci, Michael M. Bronstein, Alexander M. Bronstein, Jürgen Schmidhuber:
Multimodal similarity-preserving hashing. CoRR abs/1207.1522 (2012) - [i13]Davide Eynard, Klaus Glashoff, Michael M. Bronstein, Alexander M. Bronstein:
Multimodal diffusion geometry by joint diagonalization of Laplacians. CoRR abs/1209.2295 (2012) - [i12]Jonathan Pokrass, Alexander M. Bronstein, Michael M. Bronstein, Pablo Sprechmann, Guillermo Sapiro:
Sparse Modeling of Intrinsic Correspondences. CoRR abs/1209.6560 (2012) - [i11]Artiom Kovnatsky, Michael M. Bronstein, Alexander M. Bronstein, Klaus Glashoff, Ron Kimmel:
Coupled quasi-harmonic bases. CoRR abs/1210.0026 (2012) - 2011
- [j26]Roee Litman, Alexander M. Bronstein, Michael M. Bronstein:
Diffusion-geometric maximally stable component detection in deformable shapes. Comput. Graph. 35(3): 549-560 (2011) - [j25]Dan Raviv, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Nir A. Sochen:
Affine-invariant geodesic geometry of deformable 3D shapes. Comput. Graph. 35(3): 692-697 (2011) - [j24]Michael M. Bronstein, Alexander M. Bronstein:
Shape Recognition with Spectral Distances. IEEE Trans. Pattern Anal. Mach. Intell. 33(5): 1065-1071 (2011) - [j23]Ron Kimmel, Cuiping Zhang, Alexander M. Bronstein, Michael M. Bronstein:
Are MSER Features Really Interesting? IEEE Trans. Pattern Anal. Mach. Intell. 33(11): 2316-2320 (2011) - [j22]Michael M. Bronstein:
Lazy Sliding Window Implementation of the Bilateral Filter on Parallel Architectures. IEEE Trans. Image Process. 20(6): 1751-1756 (2011) - [j21]Alexander M. Bronstein, Michael M. Bronstein, Leonidas J. Guibas, Maks Ovsjanikov:
Shape google: Geometric words and expressions for invariant shape retrieval. ACM Trans. Graph. 30(1): 1:1-1:20 (2011) - [c49]Edmond Boyer, Alexander M. Bronstein, Michael M. Bronstein, Benjamin Bustos, Tal Darom, Radu Horaud, Ingrid Hotz, Yosi Keller, Johannes Keustermans, Artiom Kovnatsky, Roee Litman, Jan Reininghaus, Ivan Sipiran, Dirk Smeets, Paul Suetens, Dirk Vandermeulen, Andrei Zaharescu, Valentin Zobel:
SHREC '11: Robust Feature Detection and Description Benchmark. 3DOR@Eurographics 2011: 71-78 - [c48]Dan Raviv, Michael M. Bronstein, Alexander M. Bronstein, Ron Kimmel, Nir A. Sochen:
Affine-invariant diffusion geometry for the analysis of deformable 3D shapes. CVPR 2011: 2361-2367 - [c47]Fabrice Michel, Michael M. Bronstein, Alexander M. Bronstein, Nikos Paragios:
Boosted metric learning for 3D multi-modal deformable registration. ISBI 2011: 1209-1214 - [c46]Chaohui Wang, Michael M. Bronstein, Alexander M. Bronstein, Nikos Paragios:
Discrete Minimum Distortion Correspondence Problems for Non-rigid Shape Matching. SSVM 2011: 580-591 - [c45]Jonathan Pokrass, Alexander M. Bronstein, Michael M. Bronstein:
A Correspondence-Less Approach to Matching of Deformable Shapes. SSVM 2011: 592-603 - [c44]Artiom Kovnatsky, Michael M. Bronstein, Alexander M. Bronstein, Ron Kimmel:
Photometric Heat Kernel Signatures. SSVM 2011: 616-627 - [c43]Amit Hooda, Michael M. Bronstein, Alexander M. Bronstein, Radu Horaud:
Shape Palindromes: Analysis of Intrinsic Symmetries in 2D Articulated Shapes. SSVM 2011: 665-676 - [c42]Yonathan Aflalo, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Deformable Shape Retrieval by Learning Diffusion Kernels. SSVM 2011: 689-700 - [c41]Guy Rosman, Michael M. Bronstein, Alexander M. Bronstein, Alon Wolf, Ron Kimmel:
Group-Valued Regularization Framework for Motion Segmentation of Dynamic Non-rigid Shapes. SSVM 2011: 725-736 - [c40]Dan Raviv, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Nir A. Sochen:
Equi-affine Invariant Geometries of Articulated Objects. Theoretical Foundations of Computer Vision 2011: 177-190 - [i10]Artiom Kovnatsky, Michael M. Bronstein, Alexander M. Bronstein, Ron Kimmel:
Diffusion framework for geometric and photometric data fusion in non-rigid shape analysis. CoRR abs/1101.4301 (2011) - [i9]Jonathan Pokrass, Alexander M. Bronstein, Michael M. Bronstein:
A correspondence-less approach to matching of deformable shapes. CoRR abs/1101.5687 (2011) - [i8]Edmond Boyer, Alexander M. Bronstein, Michael M. Bronstein, Benjamin Bustos, Tal Darom, Radu Horaud, Ingrid Hotz, Yosi Keller, Johannes Keustermans, Artiom Kovnatsky, Roee Litman, Jan Reininghaus, Ivan Sipiran, Dirk Smeets, Paul Suetens, Dirk Vandermeulen, Andrei Zaharescu, Valentin Zobel:
SHREC 2011: robust feature detection and description benchmark. CoRR abs/1102.4258 (2011) - [i7]Michael M. Bronstein:
Kernel diff-hash. CoRR abs/1111.0466 (2011) - [i6]Michael M. Bronstein:
Multimodal diff-hash. CoRR abs/1111.1461 (2011) - [i5]Jonathan Masci, Davide Migliore, Michael M. Bronstein, Jürgen Schmidhuber:
Descriptor learning for omnidirectional image matching. CoRR abs/1112.6291 (2011) - 2010
- [j20]Dan Raviv, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Full and Partial Symmetries of Non-rigid Shapes. Int. J. Comput. Vis. 89(1): 18-39 (2010) - [j19]Guy Rosman, Michael M. Bronstein, Alexander M. Bronstein, Ron Kimmel:
Nonlinear Dimensionality Reduction by Topologically Constrained Isometric Embedding. Int. J. Comput. Vis. 89(1): 56-68 (2010) - [j18]Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Mona Mahmoudi, Guillermo Sapiro:
A Gromov-Hausdorff Framework with Diffusion Geometry for Topologically-Robust Non-rigid Shape Matching. Int. J. Comput. Vis. 89(2-3): 266-286 (2010) - [c39]Alexander M. Bronstein, Michael M. Bronstein, Umberto Castellani, Bianca Falcidieno, Andrea Fusiello, Afzal Godil, Leonidas J. Guibas, Iasonas Kokkinos, Zhouhui Lian, Maks Ovsjanikov, Giuseppe Patanè, Michela Spagnuolo, Roberto Toldo:
SHREC'10 Track: Robust Shape Retrieval. 3DOR@Eurographics 2010: 71-78 - [c38]Alexander M. Bronstein, Michael M. Bronstein, Benjamin Bustos, Umberto Castellani, Marco Cristani, Bianca Falcidieno, Leonidas J. Guibas, Iasonas Kokkinos, Vittorio Murino, Maks Ovsjanikov, Giuseppe Patanè, Ivan Sipiran, Michela Spagnuolo, Jian Sun:
SHREC'10 Track: Feature Detection and Description. 3DOR@Eurographics 2010: 79-86 - [c37]Alexander M. Bronstein, Michael M. Bronstein, Umberto Castellani, Anastasia Dubrovina, Leonidas J. Guibas, Radu Horaud, Ron Kimmel, David Knossow, Etienne von Lavante, Diana Mateus, Maks Ovsjanikov, Avinash Sharma:
SHREC'10 Track: Correspondence Finding. 3DOR@Eurographics 2010: 87-91 - [c36]Michael M. Bronstein, Iasonas Kokkinos:
Scale-invariant heat kernel signatures for non-rigid shape recognition. CVPR 2010: 1704-1711 - [c35]Michael M. Bronstein, Alexander M. Bronstein, Fabrice Michel, Nikos Paragios:
Data fusion through cross-modality metric learning using similarity-sensitive hashing. CVPR 2010: 3594-3601 - [c34]Alexander M. Bronstein, Michael M. Bronstein:
Spatially-Sensitive Affine-Invariant Image Descriptors. ECCV (2) 2010: 197-208 - [c33]Niloy J. Mitra, Alexander M. Bronstein, Michael M. Bronstein:
Intrinsic Regularity Detection in 3D Geometry. ECCV (3) 2010: 398-410 - [c32]Dan Raviv, Michael M. Bronstein, Alexander M. Bronstein, Ron Kimmel:
Volumetric heat kernel signatures. 3DOR@MM 2010: 39-44 - [i4]Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
The Video Genome. CoRR abs/1003.5320 (2010) - [i3]Roee Litman, Alexander M. Bronstein, Michael M. Bronstein:
Diffusion-geometric maximally stable component detection in deformable shapes. CoRR abs/1012.3951 (2010) - [i2]Dan Raviv, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Nir A. Sochen:
Affine-invariant diffusion geometry for the analysis of deformable 3D shapes. CoRR abs/1012.5933 (2010) - [i1]Dan Raviv, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Nir A. Sochen:
Affine-invariant geodesic geometry of deformable 3D shapes. CoRR abs/1012.5936 (2010)
2000 – 2009
- 2009
- [b2]Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Numerical Geometry of Non-Rigid Shapes. Monographs in Computer Science, Springer 2009, ISBN 978-0-387-73300-5, pp. 1-277 - [j17]Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Topology-Invariant Similarity of Nonrigid Shapes. Int. J. Comput. Vis. 81(3): 281-301 (2009) - [j16]Alexander M. Bronstein, Michael M. Bronstein, Alfred M. Bruckstein, Ron Kimmel:
Partial Similarity of Objects, or How to Compare a Centaur to a Horse. Int. J. Comput. Vis. 84(2): 163-183 (2009) - [j15]Alexander M. Bronstein, Michael M. Bronstein, Yair Carmon, Ron Kimmel:
Partial Similarity of Shapes Using a Statistical Significance Measure. IPSJ Trans. Comput. Vis. Appl. 1: 105-114 (2009) - [c31]Yohai S. Devir, Guy Rosman, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
On reconstruction of non-rigid shapes with intrinsic regularization. ICCV Workshops 2009: 272-279 - [c30]Maks Ovsjanikov, Alexander M. Bronstein, Michael M. Bronstein, Leonidas J. Guibas:
Shape Google: a computer vision approach to isometry invariant shape retrieval. ICCV Workshops 2009: 320-327 - [c29]O. Rubinstein, Yaron Honen, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
3D-color video camera. ICCV Workshops 2009: 1505-1509 - 2008
- [j14]Alexander M. Bronstein, Michael M. Bronstein, Alfred M. Bruckstein, Ron Kimmel:
Analysis of Two-Dimensional Non-Rigid Shapes. Int. J. Comput. Vis. 78(1): 67-88 (2008) - [j13]Ofir Weber, Yohai S. Devir, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Parallel algorithms for approximation of distance maps on parametric surfaces. ACM Trans. Graph. 27(4): 104:1-104:16 (2008) - [c28]Alexander M. Bronstein, Michael M. Bronstein:
Not only size matters: Regularized partial matching of nonrigid shapes. CVPR Workshops 2008: 1-6 - [c27]Alexander M. Bronstein, Michael M. Bronstein:
Regularized Partial Matching of Rigid Shapes. ECCV (2) 2008: 143-154 - 2007
- [b1]Michael M. Bronstein:
Isometry-invariant surface matching: numerical algorithms and applications. Technion - Israel Institute of Technology, Israel, 2007 - [j12]Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Weighted distance maps computation on parametric three-dimensional manifolds. J. Comput. Phys. 225(1): 771-784 (2007) - [j11]Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Expression-Invariant Representations of Faces. IEEE Trans. Image Process. 16(1): 188-197 (2007) - [j10]Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Calculus of Nonrigid Surfaces for Geometry and Texture Manipulation. IEEE Trans. Vis. Comput. Graph. 13(5): 902-913 (2007) - [c26]Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Rock, Paper, and Scissors: extrinsic vs. intrinsic similarity of non-rigid shapes. ICCV 2007: 1-6 - [c25]Dan Raviv, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Symmetries of non-rigid shapes. ICCV 2007: 1-7 - [c24]Alexander M. Bronstein, Michael M. Bronstein, Alfred M. Bruckstein, Ron Kimmel:
Paretian Similarity for Partial Comparison of Non-rigid Objects. SSVM 2007: 264-275 - 2006
- [j9]Michael M. Bronstein, Alexander M. Bronstein, Ron Kimmel, Irad Yavneh:
Multigrid multidimensional scaling. Numer. Linear Algebra Appl. 13(2-3): 149-171 (2006) - [j8]Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Efficient Computation of Isometry-Invariant Distances Between Surfaces. SIAM J. Sci. Comput. 28(5): 1812-1836 (2006) - [c23]Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Facetoface: An Isometric Model for Facial Animation. AMDO 2006: 38-47 - [c22]Alexander M. Bronstein, Michael M. Bronstein, Alfred M. Bruckstein, Ron Kimmel:
Matching Two-Dimensional Articulated Shapes Using Generalized Multidimensional Scaling. AMDO 2006: 48-57 - [c21]Guy Rosman, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Topologically Constrained Isometric Embedding. Human Motion 2006: 243-262 - [c20]Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Robust Expression-Invariant Face Recognition from Partially Missing Data. ECCV (3) 2006: 396-408 - [c19]Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky:
On Separation of Semitransparent Dynamic Images from Static Background. ICA 2006: 934-940 - 2005
- [j7]Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Three-Dimensional Face Recognition. Int. J. Comput. Vis. 64(1): 5-30 (2005) - [j6]Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi:
Sparse ICA for blind separation of transmitted and reflected images. Int. J. Imaging Syst. Technol. 15(1): 84-91 (2005) - [j5]Michael M. Bronstein, Alexander M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi:
Blind deconvolution of images using optimal sparse representations. IEEE Trans. Image Process. 14(6): 726-736 (2005) - [j4]Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky:
Relative optimization for blind deconvolution. IEEE Trans. Signal Process. 53(6): 2018-2026 (2005) - [j3]Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky:
Quasi maximum likelihood MIMO blind deconvolution: Super- and sub-Gaussianity versus consistency. IEEE Trans. Signal Process. 53(7): 2576-2579 (2005) - [c18]Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi:
Blind separation of tissues in multi-modal MRI using Sparse Component Analysis. EUSIPCO 2005: 1-4 - [c17]Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Expression-invariant face recognition via spherical embedding. ICIP (3) 2005: 756-759 - [c16]Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi:
"Unmixing" tissues: sparse component analysis in multi-contrast MRI. ICIP (2) 2005: 1282-1285 - [c15]Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Isometric Embedding of Facial Surfaces into. Scale-Space 2005: 622-631 - 2004
- [j2]Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky:
Blind source separation using block-coordinate relative Newton method. Signal Process. 84(8): 1447-1459 (2004) - [c14]Alexander M. Bronstein, Michael M. Bronstein, Alon Spira, Ron Kimmel:
Face Recognition from Facial Surface Metric. ECCV (2) 2004: 225-237 - [c13]Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky:
Blind Source Separation Using the Block-Coordinate Relative Newton Method. ICA 2004: 406-413 - [c12]Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi:
Optimal Sparse Representations for Blind Deconvolution of Images. ICA 2004: 500-507 - [c11]Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky:
Blind Deconvolution Using the Relative Newton Method. ICA 2004: 554-561 - [c10]Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi:
QML Blind Deconvolution: Asymptotic Analysis. ICA 2004: 677-684 - [c9]Alexander M. Bronstein, Michael M. Bronstein, Eyal Gordon, Ron Kimmel:
Fusion of 2D and 3D data in three-dimensional face recognition. ICIP 2004: 87-90 - [c8]Alexander M. Bronstein, Michael Zibulevsky, Michael M. Bronstein, Yehoshua Y. Zeevi:
Fast relative newton algorithm for blind deconvolution of images. ICIP 2004: 1233-1236 - [c7]Michael M. Bronstein, Alexander M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi:
Optimal sparse representations for blind source separation and blind deconvolution: a learning approach. ICIP 2004: 1815-1818 - [c6]Michael M. Bronstein, Alexander M. Bronstein, Yehoshua Y. Zeevi, Michael Zibulevsky:
Quasi-Maximum Likelihood Blind Deconvolution of Images Acquired Through Scattering Media. ISBI 2004: 352-355 - 2003
- [c5]Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Expression-Invariant 3D Face Recognition. AVBPA 2003: 62-69 - [c4]Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi:
Separation of semireflective layers using sparse ICA. ICASSP (3) 2003: 733-736 - [c3]Michael M. Bronstein, Alexander M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi:
Separation of reflections via sparse ICA. ICIP (1) 2003: 313-316 - 2002
- [j1]Michael M. Bronstein, Alexander M. Bronstein, Michael Zibulevsky, Haim Azhari:
Reconstruction in Diffraction Ultrasound Tomography Using Non-Uniform FFT. IEEE Trans. Medical Imaging 21(11): 1395-1401 (2002) - [c2]Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, Yehoshua Y. Zeevi:
Optimal nonlinear estimation of photon coordinates in PET. ISBI 2002: 541-544 - [c1]Michael M. Bronstein, Alexander M. Bronstein, Michael Zibulevsky:
Iterative reconstruction in diffraction tomography using nonuniform fast Fourier transform. ISBI 2002: 633-636
Coauthor Index
Joey Bose
aka: Avishek Joey Bose
aka: Avishek Joey Bose
Alexander M. Bronstein
aka: Alex M. Bronstein
aka: Alex M. Bronstein
[j54] [i68] [i57] [j52] [c102] [c94] [c90] [i40] [j44] [c88] [c87] [c84] [c82] [c80] [i37] [i33] [i32] [i31] [j41] [j40] [j39] [c68] [p5] [j36] [r1] [j34] [j33] [j32] [c62] [c61] [c59] [j31] [j30] [c58] [p3] [p2] [j29] [j27] [c56] [c55] [c54] [c53] [c52] [c51] [c50] [p1] [e2] [e1] [i14] [i13] [i12] [i11] [j26] [j25] [j24] [j23] [j21] [c49] [c48] [c47] [c46] [c45] [c44] [c43] [c42] [c41] [c40] [i10] [i9] [i8] [j20] [j19] [j18] [c39] [c38] [c37] [c35] [c34] [c33] [c32] [i4] [i3] [i2] [i1] [b2] [j17] [j16] [j15] [c31] [c30] [c29] [j14] [j13] [c28] [c27] [j12] [j11] [j10] [c26] [c25] [c24] [j9] [j8] [c23] [c22] [c21] [c20] [c19] [j7] [j6] [j5] [j4] [j3] [c18] [c17] [c16] [c15] [j2] [c14] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [c6] [c5] [c4] [c3] [j1] [c2] [c1]
[j54] [c102] [c88] [i33] [j33] [j31] [p2] [c56] [c55] [c52] [i11] [j25] [j23] [c48] [c44] [c42] [c41] [c40] [i10] [j20] [j19] [j18] [c37] [c32] [i4] [i2] [i1] [b2] [j17] [j16] [j15] [c31] [c29] [j14] [j13] [j12] [j11] [j10] [c26] [c25] [c24] [j9] [j8] [c23] [c22] [c21] [c20] [j7] [c17] [c15] [c14] [c9] [c5]
Maks Ovsjanikov
aka: Maksim Ovsjanikov
aka: Maksim Ovsjanikov
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