| Efficient object localization using convolutional networks J Tompson, R Goroshin, A Jain, Y LeCun, C Bregler Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 733 | 2015 |
| Learning to navigate in complex environments P Mirowski, R Pascanu, F Viola, H Soyer, AJ Ballard, A Banino, M Denil, ... arXiv preprint arXiv:1611.03673, 2016 | 451 | 2016 |
| Vector-based navigation using grid-like representations in artificial agents A Banino, C Barry, B Uria, C Blundell, T Lillicrap, P Mirowski, A Pritzel, ... Nature 557 (7705), 429-433, 2018 | 256 | 2018 |
| Stacked What-Where Auto-encoders J Zhao, M Mathieu, R Goroshin, Y LeCun https://arxiv.org/abs/1506.02351, 2016 | 226 | 2016 |
| Unsupervised learning of spatiotemporally coherent metrics R Goroshin, J Bruna, J Tompson, D Eigen, Y LeCun Proceedings of the IEEE international conference on computer vision, 4086-4093, 2015 | 102 | 2015 |
| Unsupervised learning of spatiotemporally coherent metrics R Goroshin, J Bruna, J Tompson, D Eigen, Y LeCun Proceedings of the IEEE international conference on computer vision, 4086-4093, 2015 | 102 | 2015 |
| Learning to linearize under uncertainty R Goroshin, MF Mathieu, Y LeCun Advances in Neural Information Processing Systems, 1234-1242, 2015 | 99 | 2015 |
| Meta-dataset: A dataset of datasets for learning to learn from few examples E Triantafillou, T Zhu, V Dumoulin, P Lamblin, U Evci, K Xu, R Goroshin, ... arXiv preprint arXiv:1903.03096, 2019 | 87 | 2019 |
| Saturating auto-encoders R Goroshin, Y LeCun arXiv preprint arXiv:1301.3577, 2013 | 45 | 2013 |
| Unsupervised feature learning from temporal data R Goroshin, J Bruna, J Tompson, D Eigen, Y LeCun arXiv preprint arXiv:1504.02518, 2015 | 40 | 2015 |
| Stacked whatwhere auto-encoders J Zhao, M Mathieu, R Goroshin, Y Lecun CoRR, vol. abs/1506.02351, 2015 | 19 | 2015 |
| Approximate solutions to several visibility optimization problems R Goroshin, Q Huynh, HM Zhou Communications in Mathematical Sciences 9 (2), 535-550, 2011 | 16 | 2011 |
| Automated cable tracking in sonar imagery JC Isaacs, R Goroshin OCEANS 2010 MTS/IEEE SEATTLE, 1-7, 2010 | 6 | 2010 |
| Obstacle detection using a monocular camera R Goroshin Georgia Institute of Technology, 2008 | 3 | 2008 |
| Unsupervised Feature Learning in Computer Vision R Goroshin New York University, 2015 | 2 | 2015 |
| Automated cable detection in sonar imagery JC Isaacs, R Goroshin 2009 IEEE International Conference on Systems, Man and Cybernetics, 2745-2750, 2009 | 1 | 2009 |
| An Analysis of Object Representations in Deep Visual Trackers R Goroshin, J Tompson, D Dwibedi arXiv preprint arXiv:2001.02593, 2020 | | 2020 |
| Inducing Stronger Object Representations in Deep Visual Trackers R Goroshin, J Tompson, D Dwibedi | | 2019 |
| Vector-based Navigation using Grid-like Representations in Artificial Agents. A Pritzel, A Banino, B Uria, BC Zhang, C Barry, C Blundell, C Beattie, ... | | 2018 |
| Tracking cables in sonar and optical imagery JC Isaacs, R Goroshin 2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR), 1-7, 2010 | | 2010 |
Yann LeCunChief AI Scientist at Facebook & Silver Professor at the Courant Institute, New York UniversityVerified email at cs.nyu.edu
