| Deep sets M Zaheer, S Kottur, S Ravanbakhsh, B Poczos, RR Salakhutdinov, ... Advances in neural information processing systems 30, 2017 | 2357 | 2017 |
| Accurate, fully-automated NMR spectral profiling for metabolomics S Ravanbakhsh, P Liu, R Mandal, JR Grant, M Wilson, R Eisner, ... PLoS ONE 10 (5), e0124219, 2015 | 293 | 2015 |
| Equivariance Through Parameter-Sharing S Ravanbakhsh, J Schneider, B Poczos International Conference on Machine Learning (ICML) 70, 2892--2901, 2017 | 212 | 2017 |
| CMU DeepLens: deep learning for automatic image-based galaxy–galaxy strong lens finding F Lanusse, Q Ma, N Li, TE Collett, CL Li, S Ravanbakhsh, R Mandelbaum, ... Monthly Notices of the Royal Astronomical Society 473 (3), 3895-3906, 2018 | 203 | 2018 |
| Learning to predict the cosmological structure formation S He, Y Li, Y Feng, S Ho, S Ravanbakhsh, W Chen, B Póczos Proceedings of the National Academy of Sciences 116 (28), 13825-13832, 2019 | 200 | 2019 |
| Deep learning with sets and point clouds S Ravanbakhsh, J Schneider, B Poczos International Conference on Learning Representations (ICLR) - workshop track, 2016 | 200 | 2016 |
| Deep models of interactions across sets J Hartford, DR Graham, K Leyton-Brown, S Ravanbakhsh International Conference on Machine Learning 80, 1909-1918, 2018 | 150 | 2018 |
| Estimating cosmological parameters from the dark matter distribution S Ravanbakhsh, J Oliva, S Fromenteau, L Price, S Ho, J Schneider, ... International Conference on Machine Learning, 2407-2416, 2016 | 85 | 2016 |
| Enabling dark energy science with deep generative models of galaxy images S Ravanbakhsh, F Lanusse, R Mandelbaum, J Schneider, B Poczos AAAI Conference on Artificial Intelligence, 1488-1494, 2017 | 64 | 2017 |
| Boolean Matrix Factorization and Noisy Completion via Message Passing. S Ravanbakhsh, R Barnabas Poczos, Greiner International Conference on Machine Learning (ICML), 945-954, 2016 | 52 | 2016 |
| Deep generative models for galaxy image simulations F Lanusse, R Mandelbaum, S Ravanbakhsh, CL Li, P Freeman, B Póczos Monthly Notices of the Royal Astronomical Society 504 (4), 5543-5555, 2021 | 46 | 2021 |
| Universal Equivariant Multilayer Perceptrons S Ravanbakhsh International Conference on Machine Learning (ICML), 2020 | 44 | 2020 |
| Improved knowledge graph embedding using background taxonomic information B Fatemi, S Ravanbakhsh, D Poole Proceedings of the AAAI conference on artificial intelligence 33 (01), 3526-3533, 2019 | 37 | 2019 |
| Stochastic Neural Networks with Monotonic Activation Functions S Ravanbakhsh, B Poczos, J Schneider, D Schuurmans, R Greiner 19th International Conference on Artificial Intelligence and Statistics 41 …, 2016 | 29 | 2016 |
| Incidence networks for geometric deep learning M Albooyeh, D Bertolini, S Ravanbakhsh International Conference on Machine Learning, 2020 | 26 | 2020 |
| SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks C Morris, G Rattan, S Kiefer, S Ravanbakhsh International Conference on Machine Learning, 2022 | 25 | 2022 |
| Recovering the wedge modes lost to 21-cm foregrounds S Gagnon-Hartman, Y Cui, A Liu, S Ravanbakhsh Monthly Notices of the Royal Astronomical Society 504 (4), 4716-4729, 2021 | 21 | 2021 |
| Equivariant Networks for Hierarchical Structures R Wang, M Albooyeh, S Ravanbakhsh Advances in Neural Information Processing Systems 33, 13806--13817, 2020 | 20* | 2020 |
| Subject2Vec: generative-discriminative approach from a set of image patches to a vector S Singla, M Gong, S Ravanbakhsh, F Sciurba, B Poczos, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 20 | 2018 |
| Perturbed Message Passing for Constraint Satisfaction Problems S Ravanbakhsh, R Greiner Journal of Machine Learning Research 16, 1249-1274, 2015 | 20 | 2015 |
Barnabas PoczosAssociate professor, Carnegie Mellon Universitycs.cmu.edu의 이메일 확인됨
