| The loss surfaces of multilayer networks A Choromanska, M Henaff, M Mathieu, GB Arous, Y LeCun Artificial intelligence and statistics, 192-204, 2015 | 1018 | 2015 |
| Deep convolutional networks on graph-structured data M Henaff, J Bruna, Y LeCun arXiv preprint arXiv:1506.05163, 2015 | 965 | 2015 |
| Fast Training of Convolutional Networks through FFTs M Mathieu, M Henaff, Y LeCun International Conference on Learning Representations (ICLR 2014), 2013 | 493 | 2013 |
| Tracking the World State with Recurrent Entity Networks M Henaff, J Weston, A Szlam, A Bordes, Y LeCun International Conference on Learning Representations (ICLR 2017), 2017 | 171 | 2017 |
| Unsupervised learning of sparse features for scalable audio classification. M Henaff, K Jarrett, K Kavukcuoglu, Y LeCun ISMIR 11 (445), 2011, 2011 | 154 | 2011 |
| Recurrent Orthogonal Networks and Long-Memory Tasks M Henaff, A Szlam, Y LeCun International Conference on Machine Learning, 2034-2042, 2016 | 114* | 2016 |
| A comprehensive evaluation of multicategory classification methods for microbiomic data A Statnikov, M Henaff, V Narendra, K Konganti, Z Li, L Yang, Z Pei, ... Microbiome 1 (1), 1-12, 2013 | 109 | 2013 |
| Microbiomic signatures of psoriasis: feasibility and methodology comparison A Statnikov, AV Alekseyenko, Z Li, M Henaff, GI Perez-Perez, MJ Blaser, ... Scientific reports 3 (1), 1-7, 2013 | 74 | 2013 |
| Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic M Henaff, A Canziani, Y LeCun International Conference on Learning Representations (ICLR 2019), 2019 | 47 | 2019 |
| Information content and analysis methods for multi-modal high-throughput biomedical data B Ray, M Henaff, S Ma, E Efstathiadis, ER Peskin, M Picone, T Poli, ... Scientific reports 4 (1), 1-10, 2014 | 37 | 2014 |
| Model-Based Planning with Discrete and Continuous Actions M Henaff, WF Whitney, Y LeCun arXiv preprint arXiv:1705.07177, 2018 | 34* | 2018 |
| New methods for separating causes from effects in genomics data A Statnikov, M Henaff, NI Lytkin, CF Aliferis BMC genomics 13 (8), 1-16, 2012 | 34 | 2012 |
| Kinematic state abstraction and provably efficient rich-observation reinforcement learning D Misra, M Henaff, A Krishnamurthy, J Langford International conference on machine learning, 6961-6971, 2020 | 22 | 2020 |
| Disagreement Regularized Imitation Learning K Brantley, W Sun, M Henaff International Conference on Learning Representations (ICLR 2020), 2020 | 19 | 2020 |
| Ultra-scalable and efficient methods for hybrid observational and experimental local causal pathway discovery A Statnikov, S Ma, M Henaff, N Lytkin, E Efstathiadis, ER Peskin, ... The Journal of Machine Learning Research 16 (1), 3219-3267, 2015 | 14 | 2015 |
| Prediction under uncertainty with error-encoding networks M Henaff, J Zhao, Y LeCun arXiv preprint arXiv:1711.04994, 2017 | 13 | 2017 |
| Explicit Explore-Exploit Algorithms in Continuous State Spaces M Henaff Advances in Neural Information Processing Systems, 9372-9382, 2019 | 10 | 2019 |
| PC-PG: Policy cover directed exploration for provable policy gradient learning A Agarwal, M Henaff, S Kakade, W Sun arXiv preprint arXiv:2007.08459, 2020 | 9 | 2020 |
| Deep Networks for Forward Prediction and Planning M Henaff New York University, 2018 | 1 | 2018 |
Yann LeCunChief AI Scientist at Facebook & Silver Professor at the Courant Institute, New York UniversityVerified email at cs.nyu.edu
