| An introduction to variational methods for graphical models MI Jordan, Z Ghahramani, TS Jaakkola, LK Saul Machine learning 37 (2), 183-233, 1999 | 5271 | 1999 |
| A deep learning approach to antibiotic discovery JM Stokes, K Yang, K Swanson, W Jin, A Cubillos-Ruiz, NM Donghia, ... Cell 180 (4), 688-702. e13, 2020 | 2879 | 2020 |
| De novo design of protein structure and function with RFdiffusion JL Watson, D Juergens, NR Bennett, BL Trippe, J Yim, HE Eisenach, ... Nature 620 (7976), 1089-1100, 2023 | 2144 | 2023 |
| Exploiting generative models in discriminative classifiers T Jaakkola, D Haussler Advances in neural information processing systems 11, 1998 | 2139 | 1998 |
| Junction tree variational autoencoder for molecular graph generation W Jin, R Barzilay, T Jaakkola International conference on machine learning, 2323-2332, 2018 | 2132 | 2018 |
| Analyzing learned molecular representations for property prediction K Yang, K Swanson, W Jin, C Coley, P Eiden, H Gao, A Guzman-Perez, ... Journal of chemical information and modeling 59 (8), 3370-3388, 2019 | 2113 | 2019 |
| Convergence of stochastic iterative dynamic programming algorithms T Jaakkola, M Jordan, S Singh Advances in neural information processing systems 6, 1993 | 1495 | 1993 |
| Towards robust interpretability with self-explaining neural networks D Alvarez Melis, T Jaakkola Advances in neural information processing systems 31, 2018 | 1485 | 2018 |
| Maximum-margin matrix factorization N Srebro, J Rennie, T Jaakkola Advances in neural information processing systems 17, 2004 | 1479 | 2004 |
| Convergence results for single-step on-policy reinforcement-learning algorithms S Singh, T Jaakkola, ML Littman, C Szepesvári Machine learning 38 (3), 287-308, 2000 | 1122 | 2000 |
| Rationalizing neural predictions T Lei, R Barzilay, T Jaakkola arXiv preprint arXiv:1606.04155, 2016 | 1100 | 2016 |
| Weighted low-rank approximations N Srebro, T Jaakkola Proceedings of the 20th international conference on machine learning (ICML …, 2003 | 1098 | 2003 |
| Variational message passing. J Winn, CM Bishop, T Jaakkola Journal of Machine Learning Research 6 (4), 2005 | 1015 | 2005 |
| Style transfer from non-parallel text by cross-alignment T Shen, T Lei, R Barzilay, T Jaakkola Advances in neural information processing systems 30, 2017 | 994 | 2017 |
| On the robustness of interpretability methods D Alvarez-Melis, TS Jaakkola arXiv preprint arXiv:1806.08049, 2018 | 965 | 2018 |
| Approximate inference in additive factorial hmms with application to energy disaggregation JZ Kolter, T Jaakkola Artificial intelligence and statistics, 1472-1482, 2012 | 915 | 2012 |
| Diffdock: Diffusion steps, twists, and turns for molecular docking G Corso, H Stärk, B Jing, R Barzilay, T Jaakkola arXiv preprint arXiv:2210.01776, 2022 | 899 | 2022 |
| Prediction of organic reaction outcomes using machine learning CW Coley, R Barzilay, TS Jaakkola, WH Green, KF Jensen ACS central science 3 (5), 434-443, 2017 | 881 | 2017 |
| Bayesian parameter estimation via variational methods TS Jaakkola, MI Jordan Statistics and Computing 10 (1), 25-37, 2000 | 867 | 2000 |
| Serial regulation of transcriptional regulators in the yeast cell cycle I Simon, J Barnett, N Hannett, CT Harbison, NJ Rinaldi, TL Volkert, ... Cell 106 (6), 697-708, 2001 | 863 | 2001 |
Regina BarzilayProfessor of EECS, MITVerified email at csail.mit.edu
