| 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 | 2014 | 2020 |
| Junction tree variational autoencoder for molecular graph generation W Jin, R Barzilay, T Jaakkola International conference on machine learning, 2323-2332, 2018 | 1665 | 2018 |
| Using lexical chains for text summarization R Barzilay, M Elhadad | 1652 | 1997 |
| 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 | 1492 | 2019 |
| Modeling local coherence: An entity-based approach R Barzilay, M Lapata Computational Linguistics 34 (1), 1-34, 2008 | 983 | 2008 |
| Rationalizing neural predictions T Lei, R Barzilay, T Jaakkola arXiv preprint arXiv:1606.04155, 2016 | 969 | 2016 |
| 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 | 907 | 2017 |
| 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 | 738 | 2023 |
| 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 | 730 | 2017 |
| A graph-convolutional neural network model for the prediction of chemical reactivity CW Coley, W Jin, L Rogers, TF Jamison, TS Jaakkola, WH Green, ... Chemical science 10 (2), 370-377, 2019 | 697 | 2019 |
| Extracting paraphrases from a parallel corpus R Barzilay, K McKeown Proceedings of the 39th annual meeting of the Association for Computational …, 2001 | 688 | 2001 |
| A deep learning mammography-based model for improved breast cancer risk prediction A Yala, C Lehman, T Schuster, T Portnoi, R Barzilay Radiology 292 (1), 60-66, 2019 | 675 | 2019 |
| Learning to paraphrase: An unsupervised approach using multiple-sequence alignment R Barzilay, L Lee arXiv preprint cs/0304006, 2003 | 645 | 2003 |
| Sentence fusion for multidocument news summarization R Barzilay, KR McKeown Computational Linguistics 31 (3), 297-328, 2005 | 585 | 2005 |
| Information fusion in the context of multi-document summarization R Barzilay, K McKeown, M Elhadad Proceedings of the 37th annual meeting of the Association for Computational …, 1999 | 579 | 1999 |
| Generative models for graph-based protein design J Ingraham, V Garg, R Barzilay, T Jaakkola Advances in neural information processing systems 32, 2019 | 542 | 2019 |
| Catching the drift: Probabilistic content models, with applications to generation and summarization R Barzilay, L Lee arXiv preprint cs/0405039, 2004 | 489 | 2004 |
| Language understanding for text-based games using deep reinforcement learning K Narasimhan, T Kulkarni, R Barzilay arXiv preprint arXiv:1506.08941, 2015 | 487 | 2015 |
| Convolutional embedding of attributed molecular graphs for physical property prediction CW Coley, R Barzilay, WH Green, TS Jaakkola, KF Jensen Journal of chemical information and modeling 57 (8), 1757-1772, 2017 | 479 | 2017 |
| Inferring strategies for sentence ordering in multidocument news summarization R Barzilay, N Elhadad Journal of Artificial Intelligence Research 17, 35-55, 2002 | 476 | 2002 |
