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ORCIDPietro Liò
Pietro Lió – Pietro Lio'
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- affiliation: University of Cambridge, Department of Computer Science and Technology, UK
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2020 – today
- 2023
[j123]Gabriele Ciravegna
, Pietro Barbiero, Francesco Giannini, Marco Gori, Pietro Liò, Marco Maggini, Stefano Melacci:
Logic Explained Networks. Artif. Intell. 314: 103822 (2023)- [j122]Phasit Charoenkwan, Chonlatip Pipattanaboon, Chanin Nantasenamat, Md Mehedi Hasan, Mohammad Ali Moni, Pietro Lio', Watshara Shoombuatong:
PSRTTCA: A new approach for improving the prediction and characterization of tumor T cell antigens using propensity score representation learning. Comput. Biol. Medicine 152: 106368 (2023) - [j121]Andrija Petrovic, Mladen Nikolic, Ugljesa Bugaric, Boris Delibasic, Pietro Liò:
Controlling highway toll stations using deep learning, queuing theory, and differential evolution. Eng. Appl. Artif. Intell. 119: 105683 (2023) - [j120]David Buterez, Jon Paul Janet, Steven J. Kiddle, Pietro Liò:
MF-PCBA: Multifidelity High-Throughput Screening Benchmarks for Drug Discovery and Machine Learning. J. Chem. Inf. Model. 63(9): 2667-2678 (2023) - [j119]Md. Shofiqul Islam, Khondokar Fida Hasan, Sunjida Sultana, Shahadat Uddin, Pietro Lio', Julian M. W. Quinn, Mohammad Ali Moni:
HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN. Neural Networks 162: 271-287 (2023) - [j118]Pietro Bongini, Franco Scarselli, Monica Bianchini, Giovanna Maria Dimitri, Niccolò Pancino, Pietro Lió:
Modular Multi-Source Prediction of Drug Side-Effects With DruGNN. IEEE ACM Trans. Comput. Biol. Bioinform. 20(2): 1211-1220 (2023) - [j117]Junwei Yang, Xiao-Xin Li, Feihong Liu, Dong Nie, Pietro Liò, Haikun Qi, Dinggang Shen:
Fast Multi-Contrast MRI Acquisition by Optimal Sampling of Information Complementary to Pre-Acquired MRI Contrast. IEEE Trans. Medical Imaging 42(5): 1363-1373 (2023) - [c156]Xiaofeng Lu, Xiaoyu Zhang, Pietro Lió:
GAT-DNS: DNS Multivariate Time Series Prediction Model Based on Graph Attention Network. WWW (Companion Volume) 2023: 127-131 - [c155]Gianluca Mittone, Filip Svoboda, Marco Aldinucci, Nicholas D. Lane, Pietro Lió:
A Federated Learning Benchmark for Drug-Target Interaction. WWW (Companion Volume) 2023: 1177-1181 - [i167]Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Shan Xue, Chuan Zhou, Charu C. Aggarwal, Hao Peng, Wenbin Hu, Edwin Hancock, Pietro Liò:
A Comprehensive Survey of Graph-level Learning. CoRR abs/2301.05860 (2023) - [i166]Chaitanya K. Joshi, Cristian Bodnar, Simon V. Mathis, Taco Cohen, Pietro Liò:
On the Expressive Power of Geometric Graph Neural Networks. CoRR abs/2301.09308 (2023) - [i165]Alexander Campbell, Simeon E. Spasov, Nicola Toschi, Pietro Liò:
DBGDGM: Dynamic Brain Graph Deep Generative Model. CoRR abs/2301.11408 (2023) - [i164]Xiangyu Zhao, Hannes Stärk, Dominique Beaini, Pietro Liò, Yiren Zhao:
Task-Agnostic Graph Neural Network Evaluation via Adversarial Collaboration. CoRR abs/2301.11517 (2023) - [i163]Antonio Longa, Veronica Lachi, Gabriele Santin, Monica Bianchini, Bruno Lepri, Pietro Liò, Franco Scarselli, Andrea Passerini:
Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities. CoRR abs/2302.01018 (2023) - [i162]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) - [i161]Dmitry Kazhdan, Botty Dimanov, Lucie Charlotte Magister, Pietro Barbiero, Mateja Jamnik, Pietro Liò:
GCI: A (G)raph (C)oncept (I)nterpretation Framework. CoRR abs/2302.04899 (2023) - [i160]Filip Svoboda, Gianluca Mittone, Nicholas D. Lane, Pietro Liò:
A Federated Learning Benchmark for Drug-Target Interaction. CoRR abs/2302.07684 (2023) - [i159]Jin Zhu, Guang Yang, Pietro Liò:
A residual dense vision transformer for medical image super-resolution with segmentation-based perceptual loss fine-tuning. CoRR abs/2302.11184 (2023) - [i158]Alexander Norcliffe, Bogdan Cebere, Fergus Imrie, Pietro Liò, Mihaela van der Schaar:
SurvivalGAN: Generating Time-to-Event Data for Survival Analysis. CoRR abs/2302.12749 (2023) - [i157]Md. Shofiqul Islam, Khondokar Fida Hasan, Sunjida Sultana, Shahadat Uddin, Pietro Liò, Julian M. W. Quinn, Mohammad Ali Moni:
HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN. CoRR abs/2303.06020 (2023) - [i156]Giovanna Maria Dimitri, Simeon E. Spasov, Andrea Duggento, Luca Passamonti, Pietro Liò, Nicola Toschi:
Multimodal and multicontrast image fusion via deep generative models. CoRR abs/2303.15963 (2023) - [i155]Mehedi Hasan, Moloud Abdar, Abbas Khosravi, Uwe Aickelin, Pietro Lio', Ibrahim Hossain, Ashikur Rahman, Saeid Nahavandi:
Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training Processing. CoRR abs/2304.04906 (2023) - [i154]Emma L. Ambags, Giulia Capitoli, Vincenzo L' Imperio, Michele Provenzano, Marco S. Nobile, Pietro Liò:
Assisting clinical practice with fuzzy probabilistic decision trees. CoRR abs/2304.07788 (2023) - [i153]Antonio Purificato, Giulia Cassarà, Pietro Liò, Fabrizio Silvestri:
Sheaf Neural Networks for Graph-based Recommender Systems. CoRR abs/2304.09097 (2023) - [i152]Francesco Bardozzo, Andrea Terlizzi, Pietro Liò, Roberto Tagliaferri:
ElegansNet: a brief scientific report and initial experiments. CoRR abs/2304.13538 (2023) - [i151]Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Lio', Frédéric Precioso, Mateja Jamnik, Giuseppe Marra:
Interpretable Neural-Symbolic Concept Reasoning. CoRR abs/2304.14068 (2023) - [i150]Pietro Barbiero, Stefano Fioravanti, Francesco Giannini, Alberto Tonda, Pietro Liò, Elena Di Lavore:
Categorical Foundations of Explainable AI: A Unifying Formalism of Structures and Semantics. CoRR abs/2304.14094 (2023) - [i149]King Fai Yeh, Paris D. L. Flood, William Redman, Pietro Liò:
Learning Linear Embeddings for Non-Linear Network Dynamics with Koopman Message Passing. CoRR abs/2305.09060 (2023) - [i148]Georg Wölflein, Lucie Charlotte Magister, Pietro Liò, David J. Harrison, Ognjen Arandjelovic:
Deep Multiple Instance Learning with Distance-Aware Self-Attention. CoRR abs/2305.10552 (2023) - 2022
- [j116]Ramón Viñas, Helena Andrés-Terré, Pietro Liò, Kevin Bryson:
Adversarial generation of gene expression data. Bioinform. 38(3): 730-737 (2022) - [j115]David Buterez, Ioana Bica, Ifrah Tariq, Helena Andrés-Terré, Pietro Liò:
CellVGAE: an unsupervised scRNA-seq analysis workflow with graph attention networks. Bioinform. 38(5): 1277-1286 (2022) - [j114]Paul Scherer, Maja Trebacz, Nikola Simidjievski, Ramón Viñas, Zohreh Shams, Helena Andrés-Terré, Mateja Jamnik, Pietro Liò:
Unsupervised construction of computational graphs for gene expression data with explicit structural inductive biases. Bioinform. 38(5): 1320-1327 (2022) - [j113]Phasit Charoenkwan, Nalini Schaduangrat, Mohammad Ali Moni, Pietro Lio', Balachandran Manavalan, Watshara Shoombuatong:
SAPPHIRE: A stacking-based ensemble learning framework for accurate prediction of thermophilic proteins. Comput. Biol. Medicine 146: 105704 (2022) - [j112]Phasit Charoenkwan, Nalini Schaduangrat, Pietro Lio', Mohammad Ali Moni, Balachandran Manavalan, Watshara Shoombuatong:
NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides. Comput. Biol. Medicine 148: 105700 (2022) - [j111]Helena Coggan, Helena Andrés-Terré, Pietro Liò:
A novel interpretable machine learning algorithm to identify optimal parameter space for cancer growth. Frontiers Big Data 5 (2022) - [j110]Giovanna Maria Dimitri, Simeon E. Spasov, Andrea Duggento, Luca Passamonti, Pietro Lió, Nicola Toschi:
Multimodal and multicontrast image fusion via deep generative models. Inf. Fusion 88: 146-160 (2022) - [j109]Xiaofeng Lu, Yuying Liao, Chao Liu, Pietro Liò, Pan Hui:
Heterogeneous Model Fusion Federated Learning Mechanism Based on Model Mapping. IEEE Internet Things J. 9(8): 6058-6068 (2022) - [j108]Phasit Charoenkwan, Pramote Chumnanpuen, Nalini Schaduangrat, Pietro Lio', Mohammad Ali Moni, Watshara Shoombuatong:
Improved prediction and characterization of blood-brain barrier penetrating peptides using estimated propensity scores of dipeptides. J. Comput. Aided Mol. Des. 36(11): 781-796 (2022) - [j107]Tiago Azevedo, Alexander Campbell, Rafael Romero-Garcia, Luca Passamonti, Richard A. I. Bethlehem, Pietro Liò, Nicola Toschi:
A deep graph neural network architecture for modelling spatio-temporal dynamics in resting-state functional MRI data. Medical Image Anal. 79: 102471 (2022) - [j106]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) - [j105]Yutong Chen, Carola-Bibiane Schönlieb, Pietro Liò, Tim Leiner, Pier Luigi Dragotti, Ge Wang, Daniel Rueckert, David N. Firmin, Guang Yang:
AI-Based Reconstruction for Fast MRI - A Systematic Review and Meta-Analysis. Proc. IEEE 110(2): 224-245 (2022) - [j104]Animesh Chaturvedi, Aruna Tiwari, Shubhangi Chaturvedi, Pietro Liò:
System Neural Network: Evolution and Change Based Structure Learning. IEEE Trans. Artif. Intell. 3(3): 426-435 (2022) - [c154]Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Pietro Lió, Marco Gori, Stefano Melacci:
Entropy-Based Logic Explanations of Neural Networks. AAAI 2022: 6046-6054 - [c153]Dobrik Georgiev, Pietro Barbiero, Dmitry Kazhdan, Petar Velickovic, Pietro Lió:
Algorithmic Concept-Based Explainable Reasoning. AAAI 2022: 6685-6693 - [c152]Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong:
Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets. AISTATS 2022: 4818-4834 - [c151]Felix L. Opolka, Pietro Liò:
Bayesian Link Prediction with Deep Graph Convolutional Gaussian Processes. AISTATS 2022: 4835-4852 - [c150]Xiaofeng Lu, Renyu Pang, Pietro Liò:
Poster: CFMAP: A Robust CPU Clock Fingerprint Model for Device Authentication. CCS 2022: 3407-3409 - [c149]Shea Cardozo, Gabriel Islas Montero, Dmitry Kazhdan, Botty Dimanov, Maleakhi A. Wijaya, Mateja Jamnik, Pietro Liò:
Explainer Divergence Scores (EDS): Some Post-Hoc Explanations May be Effective for Detecting Unknown Spurious Correlations. CIKM Workshops 2022 - [c148]Rishabh Jain, Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Davide Buffelli, Pietro Liò:
Extending Logic Explained Networks to Text Classification. EMNLP 2022: 8838-8857 - [c147]Alexander Campbell, Lorena Qendro, Pietro Liò, Cecilia Mascolo:
Robust and Efficient Uncertainty Aware Biosignal Classification via Early Exit Ensembles. ICASSP 2022: 3998-4002 - [c146]Shyam A. Tailor, Felix L. Opolka, Pietro Liò, Nicholas Donald Lane:
Do We Need Anisotropic Graph Neural Networks? ICLR 2022 - [c145]Junchao Fan, Jiawei Pei, Xiuli Bi, Bin Xiao, Pietro Liò:
Context Correlation Aware Network for Cardiac Segmentation. ICME 2022: 1-6 - [c144]Ben J. Day, Ramón Viñas Torné, Nikola Simidjievski, Pietro Lió:
Attentional Meta-learners for Few-shot Polythetic Classification. ICML 2022: 4867-4889 - [c143]Hannes Stärk, Dominique Beaini, Gabriele Corso, Prudencio Tossou, Christian Dallago, Stephan Günnemann, Pietro Lió:
3D Infomax improves GNNs for Molecular Property Prediction. ICML 2022: 20479-20502 - [c142]Michal Pándy, Weikang Qiu, Gabriele Corso, Petar Velickovic, Zhitao Ying, Jure Leskovec, Pietro Liò:
Learning Graph Search Heuristics. LoG 2022: 10 - [c141]Bingxin Zhou, Xinliang Liu, Yuehua Liu, Yunying Huang, Pietro Liò, Yuguang Wang:
Well-Conditioned Spectral Transforms for Dynamic Graph Representation. LoG 2022: 12 - [c140]Paul Scherer, Pietro Liò, Mateja Jamnik:
Distributed Representations of Graphs for Drug Pair Scoring. LoG 2022: 22 - [c139]Yu He, Petar Velickovic, Pietro Liò, Andreea Deac:
Continuous Neural Algorithmic Planners. LoG 2022: 54 - [c138]Pengfang Qian, Junwei Yang, Pietro Lió, Peng Hu, Haikun Qi:
Joint Group-Wise Motion Estimation and Segmentation of Cardiac Cine MR Images Using Recurrent U-Net. MIUA 2022: 65-74 - [c137]Xiaofeng Lu, Jinglun Zhao, Pietro Lió:
Robust android malware detection based on subgraph network and denoising GCN network. MobiSys 2022: 549-550 - [c136]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 - [c135]Davide Buffelli, Pietro Lió, Fabio Vandin:
SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks. NeurIPS 2022 - [c134]David Buterez, Jon Paul Janet, Steven J. Kiddle, Dino Oglic, Pietro Liò:
Graph Neural Networks with Adaptive Readouts. NeurIPS 2022 - [c133]Fergus Imrie, Alexander Norcliffe, Pietro Lió, Mihaela van der Schaar:
Composite Feature Selection Using Deep Ensembles. NeurIPS 2022 - [c132]Arian R. Jamasb, Ramón Viñas Torné, Eric Ma, Yuanqi Du, Charles Harris, Kexin Huang, Dominic Hall, Pietro Lió, Tom L. Blundell:
Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks. NeurIPS 2022 - [c131]Mateo Espinosa Zarlenga, Pietro Barbiero, Gabriele Ciravegna, Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Zohreh Shams, Frédéric Precioso, Stefano Melacci, Adrian Weller, Pietro Lió, Mateja Jamnik:
Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off. NeurIPS 2022 - [c130]Lihao Liu, Zhening Huang, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
You only Look at Patches: A Patch-wise Framework for 3D Unsupervised Medical Image Registration. WBIR 2022: 190-193 - [i147]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) - [i146]Pietro Bongini, Franco Scarselli, Monica Bianchini, Giovanna Maria Dimitri, Niccolò Pancino, Pietro Liò:
Modular multi-source prediction of drug side-effects with DruGNN. CoRR abs/2202.08147 (2022) - [i145]Charles N. Christensen, Meng Lu, Edward N. Ward, Pietro Liò, Clemens F. Kaminski:
Spatio-temporal Vision Transformer for Super-resolution Microscopy. CoRR abs/2203.00030 (2022) - [i144]Lihao Liu, Zhening Huang, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
PC-SwinMorph: Patch Representation for Unsupervised Medical Image Registration and Segmentation. CoRR abs/2203.05684 (2022) - [i143]Jiahao Huang, Yingying Fang, Yang Nan, Huanjun Wu, Yinzhe Wu, Zhifan Gao, Yang Li, Zidong Wang, Pietro Liò, Daniel Rueckert, Yonina C. Eldar, Guang Yang:
Data and Physics Driven Learning Models for Fast MRI - Fundamentals and Methodologies from CNN, GAN to Attention and Transformers. CoRR abs/2204.01706 (2022) - [i142]Christopher Wei Jin Goh, Cristian Bodnar, Pietro Liò:
Simplicial Attention Networks. CoRR abs/2204.09455 (2022) - [i141]Tolou Shadbahr, Michael Roberts, Jan Stanczuk, Julian D. Gilbey, Philip Teare, Sören Dittmer, Matthew Thorpe, Ramón Viñas Torné, Evis Sala, Pietro Lió, Mishal Patel, AIX-COVNET Collaboration, James H. F. Rudd, Tuomas Mirtti, Antti Rannikko, John A. D. Aston, Jing Tang, Carola-Bibiane Schönlieb:
Classification of datasets with imputed missing values: does imputation quality matter? CoRR abs/2206.08478 (2022) - [i140]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) - [i139]Kai Yi, Jialin Chen, Yu Guang Wang, Bingxin Zhou, Pietro Liò, Yanan Fan, Jan Hamann:
Approximate Equivariance SO(3) Needlet Convolution. CoRR abs/2206.10385 (2022) - [i138]Davide Buffelli, Pietro Liò, Fabio Vandin:
SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks. CoRR abs/2207.07888 (2022) - [i137]Lucie Charlotte Magister, Pietro Barbiero, Dmitry Kazhdan, Federico Siciliano, Gabriele Ciravegna, Fabrizio Silvestri, Pietro Liò, Mateja Jamnik:
Encoding Concepts in Graph Neural Networks. CoRR abs/2207.13586 (2022) - [i136]Han Xuanyuan, Pietro Barbiero, Dobrik Georgiev, Lucie Charlotte Magister, Pietro Lió:
Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis. CoRR abs/2208.10609 (2022) - [i135]Mateo Espinosa Zarlenga, Pietro Barbiero, Gabriele Ciravegna, Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Zohreh Shams, Frédéric Precioso, Stefano Melacci, Adrian Weller, Pietro Liò, Mateja Jamnik:
Concept Embedding Models. CoRR abs/2209.09056 (2022) - [i134]Paul Scherer, Pietro Liò, Mateja Jamnik:
Distributed representations of graphs for drug pair scoring. CoRR abs/2209.09383 (2022) - [i133]Alexander Campbell, Antonio Giuliano Zippo, Luca Passamonti, Nicola Toschi, Pietro Liò:
DBGSL: Dynamic Brain Graph Structure Learning. CoRR abs/2209.13513 (2022) - [i132]Steve Azzolin, Antonio Longa, Pietro Barbiero, Pietro Liò, Andrea Passerini:
Global Explainability of GNNs via Logic Combination of Learned Concepts. CoRR abs/2210.07147 (2022) - [i131]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) - [i130]Antonio Longa, Steve Azzolin, Gabriele Santin, Giulia Cencetti, Pietro Liò, Bruno Lepri, Andrea Passerini:
Explaining the Explainers in Graph Neural Networks: a Comparative Study. CoRR abs/2210.15304 (2022) - [i129]Fergus Imrie, Alexander Norcliffe, Pietro Liò, Mihaela van der Schaar:
Composite Feature Selection using Deep Ensembles. CoRR abs/2211.00631 (2022) - [i128]David Buterez, Jon Paul Janet, Steven J. Kiddle, Dino Oglic, Pietro Liò:
Graph Neural Networks with Adaptive Readouts. CoRR abs/2211.04952 (2022) - [i127]Andrei Margeloiu, Nikola Simidjievski, Pietro Lio', Mateja Jamnik:
Graph-Conditioned MLP for High-Dimensional Tabular Biomedical Data. CoRR abs/2211.06302 (2022) - [i126]Lihao Liu, Jean Prost, Lei Zhu, Nicolas Papadakis, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
SCOTCH and SODA: A Transformer Video Shadow Detection Framework. CoRR abs/2211.06885 (2022) - [i125]Carlos Purves, Pietro Liò, Catalina Cangea:
Goal-Conditioned Reinforcement Learning in the Presence of an Adversary. CoRR abs/2211.06929 (2022) - [i124]Shea Cardozo, Gabriel Islas Montero, Dmitry Kazhdan, Botty Dimanov, Maleakhi A. Wijaya, Mateja Jamnik, Pietro Liò:
Explainer Divergence Scores (EDS): Some Post-Hoc Explanations May be Effective for Detecting Unknown Spurious Correlations. CoRR abs/2211.07650 (2022) - [i123]Rishabh Jain, Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Davide Buffelli, Pietro Liò:
Extending Logic Explained Networks to Text Classification. CoRR abs/2211.09732 (2022) - [i122]Yana Lishkova, Paul Scherer, Steffen Ridderbusch, Mateja Jamnik, Pietro Liò, Sina Ober-Blöbaum, Christian Offen:
Discrete Lagrangian Neural Networks with Automatic Symmetry Discovery. CoRR abs/2211.10830 (2022) - [i121]Yin-Cong Zhi, Felix L. Opolka, Yin Cheng Ng, Pietro Liò, Xiaowen Dong:
Transductive Kernels for Gaussian Processes on Graphs. CoRR abs/2211.15322 (2022) - [i120]Harrison Mitchell, Alexander Norcliffe, Pietro Liò:
Learning Feynman Diagrams using Graph Neural Networks. CoRR abs/2211.15348 (2022) - [i119]Andrei Margeloiu, Nikola Simidjievski, Pietro Liò, Mateja Jamnik:
Weight Predictor Network with Feature Selection for Small Sample Tabular Biomedical Data. CoRR abs/2211.15616 (2022) - [i118]Yu He, Petar Velickovic, Pietro Liò, Andreea Deac:
Continuous Neural Algorithmic Planners. CoRR abs/2211.15839 (2022) - [i117]Haitz Sáez de Ocáriz Borde, Anees Kazi, Federico Barbero, Pietro Liò:
Latent Graph Inference using Product Manifolds. CoRR abs/2211.16199 (2022) - [i116]Michal Pándy, Weikang Qiu, Gabriele Corso, Petar Velickovic, Rex Ying, Jure Leskovec, Pietro Liò:
Learning Graph Search Heuristics. CoRR abs/2212.03978 (2022) - [i115]Aarjav Jain, Challenger Mishra, Pietro Liò:
A physics-informed search for metric solutions to Ricci flow, their embeddings, and visualisation. CoRR abs/2212.05892 (2022) - 2021
- [j103]Md. Rabiul Islam, Mohammad Ali Moni, Md. Milon Islam, Md Rashed-Al-Mahfuz, Md. Saiful Islam, Md. Kamrul Hasan, Md. Sabir Hossain, Mohiuddin Ahmad, Shahadat Uddin, A. K. M. Azad, Salem A. Alyami, Md. Atiqur Rahman Ahad, Pietro Lió:
Emotion Recognition From EEG Signal Focusing on Deep Learning and Shallow Learning Techniques. IEEE Access 9: 94601-94624 (2021) - [j102]Zulkar Nain, Humayan Kabir Rana, Pietro Liò, Sheikh Mohammed Shariful Islam, Matthew A. Summers, Mohammad Ali Moni:
Pathogenetic profiling of COVID-19 and SARS-like viruses. Briefings Bioinform. 22(2): 1175-1196 (2021) - [j101]Kexin Chen, Haoming Xu, Yiming Lei, Pietro Lió, Yuan Li, Hongyan Guo, Mohammad Ali Moni:
Integration and interplay of machine learning and bioinformatics approach to identify genetic interaction related to ovarian cancer chemoresistance. Briefings Bioinform. 22(6) (2021) - [j100]Francesco Bardozzo, Pietro Lió, Roberto Tagliaferri:
Signal metrics analysis of oscillatory patterns in bacterial multi-omic networks. Bioinform. 37(10): 1411-1419 (2021) - [j99]Andrea Tangherloni, Federico Ricciuti, Daniela Besozzi, Pietro Liò, Ana Cvejic:
Analysis of single-cell RNA sequencing data based on autoencoders. BMC Bioinform. 22(1): 309 (2021) - [j98]Daniele D'Agostino, Pietro Liò, Marco Aldinucci, Ivan Merelli:
Advantages of using graph databases to explore chromatin conformation capture experiments. BMC Bioinform. 22-S(2): 43 (2021) - [j97]Cristian Bodnar, Catalina Cangea, Pietro Liò:
Deep Graph Mapper: Seeing Graphs Through the Neural Lens. Frontiers Big Data 4: 680535 (2021) - [j96]Jin Zhu, Chuan Tan, Junwei Yang, Guang Yang, Pietro Lio':
Arbitrary Scale Super-Resolution for Medical Images. Int. J. Neural Syst. 31(10): 2150037:1-2150037:20 (2021) - [j95]Mihaela van der Schaar, Ahmed M. Alaa, R. Andres Floto, Alexander Gimson, Stefan Scholtes, Angela M. Wood, Eoin F. McKinney, Daniel Jarrett, Pietro Lió, Ari Ercole:
How artificial intelligence and machine learning can help healthcare systems respond to COVID-19. Mach. Learn. 110(1): 1-14 (2021) - [j94]Xiaofeng Lu, Songbing Fu, Cheng Jiang, Pietro Lió:
A Fine-Grained IoT Data Access Control Scheme Combining Attribute-Based Encryption and Blockchain. Secur. Commun. Networks 2021: 5308206:1-5308206:13 (2021) - [j93]