| The multiscale laplacian graph kernel R Kondor, H Pan Advances in Neural Information Processing Systems, 2990-2998, 2016 | 217 | 2016 |
| Covariant compositional networks for learning graphs R Kondor, HT Son, H Pan, B Anderson, S Trivedi arXiv preprint arXiv:1801.02144, 2018 | 148 | 2018 |
| Predicting molecular properties with covariant compositional networks TS Hy, S Trivedi, H Pan, BM Anderson, R Kondor The Journal of chemical physics 148 (24), 2018 | 96 | 2018 |
| Permutation equivariant layers for higher order interactions H Pan, R Kondor International Conference on Artificial Intelligence and Statistics, 5987-6001, 2022 | 30 | 2022 |
| Covariant compositional networks for learning graphs TS Hy, S Trivedi, H Pan, BM Anderson, R Kondor Proc. International Workshop on Mining and Learning with Graphs (MLG) 4, 2019 | 13 | 2019 |
| Molecular fingerprints are a simple yet effective solution to the drug–drug interaction problem Y Long, H Pan, C Zhang, HT Song, R Kondor, A Rzhetsky drugs 500, 1-7, 2022 | 6 | 2022 |
| Fourier Bases for Solving Permutation Puzzles H Pan, R Kondor International Conference on Artificial Intelligence and Statistics, 172-180, 2021 | 2 | 2021 |
| Leveraging Symmetry and Structure in Machine Learning H Pan The University of Chicago, 2022 | | 2022 |
| Learning Force Fields using Covariant Compositional Networks B Anderson, R Kondor, H Pan, S Trivedi, TS Hy APS 2018, F34. 011, 2018 | | 2018 |
