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Risi Kondor
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Publications
- 2023
- [i27]Zihan Pengmei, Zimu Li, Chih-chan Tien, Risi Kondor, Aaron R. Dinner:
Transformers are efficient hierarchical chemical graph learners. CoRR abs/2310.01704 (2023) - 2022
- [c29]Horace Pan, Risi Kondor:
Permutation Equivariant Layers for Higher Order Interactions. AISTATS 2022: 5987-6001 - [i26]Alexander Bogatskiy, Sanmay Ganguly, Thomas Kipf, Risi Kondor, David W. Miller, Daniel Murnane, Jan T. Offermann, Mariel Pettee, Phiala Shanahan, Chase Shimmin, Savannah Thais:
Symmetry Group Equivariant Architectures for Physics. CoRR abs/2203.06153 (2022) - [i24]Han Zheng, Zimu Li, Junyu Liu, Sergii Strelchuk, Risi Kondor:
On the Super-exponential Quantum Speedup of Equivariant Quantum Machine Learning Algorithms with SU(d) Symmetry. CoRR abs/2207.07250 (2022) - [i22]Zimu Li, Han Zheng, Erik H. Thiede, Junyu Liu, Risi Kondor:
Group-Equivariant Neural Networks with Fusion Diagrams. CoRR abs/2211.07482 (2022) - 2021
- [c26]Horace Pan, Risi Kondor:
Fourier Bases for Solving Permutation Puzzles. AISTATS 2021: 172-180 - [c25]Erik H. Thiede, Wenda Zhou, Risi Kondor:
Autobahn: Automorphism-based Graph Neural Nets. NeurIPS 2021: 29922-29934 - [c24]Raphael J. L. Townshend, Martin Vögele, Patricia Suriana, Alexander Derry, Alexander S. Powers, Yianni Laloudakis, Sidhika Balachandar, Bowen Jing, Brandon M. Anderson, Stephan Eismann, Risi Kondor, Russ B. Altman, Ron O. Dror:
ATOM3D: Tasks on Molecules in Three Dimensions. NeurIPS Datasets and Benchmarks 2021 - [i21]Erik Henning Thiede, Wenda Zhou, Risi Kondor:
Autobahn: Automorphism-based Graph Neural Nets. CoRR abs/2103.01710 (2021) - [i18]Han Zheng, Zimu Li, Junyu Liu, Sergii Strelchuk, Risi Kondor:
Speeding up Learning Quantum States through Group Equivariant Convolutional Quantum Ans{ä}tze. CoRR abs/2112.07611 (2021) - 2020
- [c23]Alexander Bogatskiy, Brandon M. Anderson, Jan T. Offermann, Marwah Roussi, David W. Miller, Risi Kondor:
Lorentz Group Equivariant Neural Network for Particle Physics. ICML 2020: 992-1002 - [i17]Erik Henning Thiede, Truong-Son Hy, Risi Kondor:
The general theory of permutation equivarant neural networks and higher order graph variational encoders. CoRR abs/2004.03990 (2020) - [i16]Alexander Bogatskiy, Brandon M. Anderson, Jan T. Offermann, Marwah Roussi, David W. Miller, Risi Kondor:
Lorentz Group Equivariant Neural Network for Particle Physics. CoRR abs/2006.04780 (2020) - [i15]Lars A. Bratholm, Will Gerrard, Brandon M. Anderson, Shaojie Bai, Sunghwan Choi, Lam Dang, Pavel Hanchar, Addison Howard, Guillaume Huard, Sanghoon Kim, J. Zico Kolter, Risi Kondor, Mordechai Kornbluth, Youhan Lee, Youngsoo Lee, Jonathan P. Mailoa, Thanh Tu Nguyen, Milos Popovic, Goran Rakocevic, Walter Reade, Wonho Song, Luka Stojanovic, Erik H. Thiede, Nebojsa Tijanic, Andres Torrubia, Devin Willmott, Craig P. Butts, David R. Glowacki, Kaggle participants:
A community-powered search of machine learning strategy space to find NMR property prediction models. CoRR abs/2008.05994 (2020) - [i14]Raphael J. L. Townshend, Martin Vögele, Patricia Suriana, Alexander Derry, Alexander S. Powers, Yianni Laloudakis, Sidhika Balachandar, Brandon M. Anderson, Stephan Eismann, Risi Kondor, Russ B. Altman, Ron O. Dror:
ATOM3D: Tasks On Molecules in Three Dimensions. CoRR abs/2012.04035 (2020) - 2019
- [c22]Brandon M. Anderson, Truong-Son Hy, Risi Kondor:
Cormorant: Covariant Molecular Neural Networks. NeurIPS 2019: 14510-14519 - [i13]Brandon M. Anderson, Truong-Son Hy, Risi Kondor:
Cormorant: Covariant Molecular Neural Networks. CoRR abs/1906.04015 (2019) - [i12]Kirk Swanson, Shubhendu Trivedi, Joshua Lequieu, Kyle Swanson, Risi Kondor:
Deep Learning for Automated Classification and Characterization of Amorphous Materials. CoRR abs/1909.04648 (2019) - [i11]Pramod Kaushik Mudrakarta, Shubhendu Trivedi, Risi Kondor:
Asymmetric Multiresolution Matrix Factorization. CoRR abs/1910.05132 (2019) - 2018
- [c21]Risi Kondor, Hy Truong Son, Horace Pan, Brandon M. Anderson, Shubhendu Trivedi:
Covariant Compositional Networks For Learning Graphs. ICLR (Workshop) 2018 - [c20]Risi Kondor, Shubhendu Trivedi:
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups. ICML 2018: 2752-2760 - [c19]Risi Kondor, Zhen Lin, Shubhendu Trivedi:
Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network. NeurIPS 2018: 10138-10147 - [i10]Risi Kondor, Hy Truong Son, Horace Pan, Brandon M. Anderson, Shubhendu Trivedi:
Covariant Compositional Networks For Learning Graphs. CoRR abs/1801.02144 (2018) - [i9]Risi Kondor, Shubhendu Trivedi:
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups. CoRR abs/1802.03690 (2018) - [i7]Risi Kondor, Zhen Lin, Shubhendu Trivedi:
Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network. CoRR abs/1806.09231 (2018) - 2016
- [c16]Nedelina Teneva, Pramod Kaushik Mudrakarta, Risi Kondor:
Multiresolution Matrix Compression. AISTATS 2016: 1441-1449 - [c15]Risi Kondor, Horace Pan:
The Multiscale Laplacian Graph Kernel. NIPS 2016: 2982-2990 - 2015
- [i3]Risi Kondor, Nedelina Teneva, Pramod Kaushik Mudrakarta:
Parallel MMF: a Multiresolution Approach to Matrix Computation. CoRR abs/1507.04396 (2015) - 2014
- [c14]Risi Kondor, Nedelina Teneva, Vikas K. Garg:
Multiresolution Matrix Factorization. ICML 2014: 1620-1628 - 2007
- [c6]Risi Kondor, Andrew G. Howard, Tony Jebara:
Multi-object tracking with representations of the symmetric group. AISTATS 2007: 211-218 - 2006
- [c5]Risi Kondor, Tony Jebara:
Gaussian and Wishart Hyperkernels. NIPS 2006: 729-736 - 2004
- [j1]Tony Jebara, Risi Kondor, Andrew G. Howard:
Probability Product Kernels. J. Mach. Learn. Res. 5: 819-844 (2004) - 2003
- [c4]Tony Jebara, Risi Kondor:
Bhattacharyya Expected Likelihood Kernels. COLT 2003: 57-71 - [c2]Risi Kondor, Tony Jebara:
A Kernel Between Sets of Vectors. ICML 2003: 361-368
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