| Generative adversarial active learning JJ Zhu, J Bento NIPS’17 Workshop: Teaching Machines, Robots, and Humans, 2017 | 230 | 2017 |
| Which graphical models are difficult to learn? J Bento, A Montanari Advances in Neural Information Processing Systems 22, 1303--1311, 2009 | 97* | 2009 |
| Learning networks of stochastic differential equations J Bento, M Ibrahimi, A Montanari Advances in Neural Information Processing Systems 23, 172--180, 2010 | 89* | 2010 |
| Strain dependent genetic networks for antibiotic-sensitivity in a bacterial pathogen with a large pan-genome T van Opijnen, S Dedrick, J Bento PLoS pathogens 12 (9), e1005869, 2016 | 65 | 2016 |
| A message-passing algorithm for multi-agent trajectory planning J Bento, N Derbinsky, J Alonso-Mora, J Yedidia Advances in Neural Information Processing Systems, 2013 | 53 | 2013 |
| An improved three-weight message-passing algorithm N Derbinsky, J Bento, V Elser, JS Yedidia arXiv preprint arXiv:1305.1961, 2013 | 47 | 2013 |
| Probabilistic document model for automated document composition N Damera-Venkata, J Bento, E O'Brien-Strain Proceedings of the 11th ACM symposium on Document engineering, 3-12, 2011 | 44 | 2011 |
| Entropy of a bacterial stress response is a generalizable predictor for fitness and antibiotic sensitivity Z Zhu, D Surujon, JC Ortiz-Marquez, W Huo, RR Isberg, J Bento, ... Nature communications 11 (1), 4365, 2020 | 42 | 2020 |
| The boundary forest algorithm for online supervised and unsupervised learning C Mathy, N Derbinsky, J Bento, J Rosenthal, J Yedidia Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 39 | 2015 |
| A family of tractable graph distances J Bento, S Ioannidis Proceedings of the 2018 SIAM International Conference on Data Mining, 333-341, 2018 | 36 | 2018 |
| An explicit rate bound for over-relaxed ADMM G França, J Bento 2016 IEEE International Symposium on Information Theory (ISIT), 2104-2108, 2016 | 34 | 2016 |
| Line‐drawing video stylization N Ben‐Zvi, J Bento, M Mahler, J Hodgins, A Shamir Computer Graphics Forum 35 (6), 18-32, 2016 | 27 | 2016 |
| CNN-Peaks: ChIP-Seq peak detection pipeline using convolutional neural networks that imitate human visual inspection D Oh, JS Strattan, JK Hur, J Bento, AE Urban, G Song, JM Cherry Scientific reports 10 (1), 7933, 2020 | 24 | 2020 |
| Shape and illumination from shading using the generic viewpoint assumption D Zoran, D Krishnan, J Bento, B Freeman Advances in Neural Information Processing Systems 27, 2014 | 23 | 2014 |
| How is distributed ADMM affected by network topology? G França, J Bento arXiv preprint arXiv:1710.00889, 2017 | 20 | 2017 |
| A metric for sets of trajectories that is practical and mathematically consistent J Bento, JJ Zhu arXiv preprint arXiv:1601.03094, 2016 | 17 | 2016 |
| Markov chain lifting and distributed ADMM G França, J Bento IEEE Signal Processing Letters 24 (3), 294-298, 2017 | 15 | 2017 |
| Testing fine-grained parallelism for the admm on a factor-graph N Hao, AR Oghbaee, M Rostami, N Derbinsky, J Bento 2016 IEEE International Parallel and Distributed Processing Symposium …, 2016 | 15 | 2016 |
| Proximal operators for multi-agent path planning J Bento, N Derbinsky, C Mathy, J Yedidia Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 15 | 2015 |
| Distributed optimization, averaging via ADMM, and network topology G França, J Bento Proceedings of the IEEE 108 (11), 1939-1952, 2020 | 14 | 2020 |
Nate DerbinskyNortheastern UniversityVerified email at northeastern.edu
