| Going deeper with convolutions C Szegedy, W Liu, Y Jia, P Sermanet, S Reed, D Anguelov, D Erhan, ... [CVPR 2015] Computer Vision and Pattern Recognition, 2015 | 50729 | 2015 |
| Overfeat: Integrated recognition, localization and detection using convolutional networks P Sermanet, D Eigen, X Zhang, M Mathieu, R Fergus, Y LeCun [ICLR 2014] International Conference on Learning Representations, 16, 2013 | 7056 | 2013 |
| Pedestrian detection with unsupervised multi-stage feature learning P Sermanet, K Kavukcuoglu, S Chintala, Y LeCun Computer Vision and Pattern Recognition (CVPR 2013), 3626-3633, 2013 | 1064 | 2013 |
| Traffic sign recognition with multi-scale convolutional networks P Sermanet, Y LeCun The 2011 international joint conference on neural networks, 2809-2813, 2011 | 956 | 2011 |
| Time-contrastive networks: Self-supervised learning from video P Sermanet, C Lynch, Y Chebotar, J Hsu, E Jang, S Schaal, S Levine, ... 2018 IEEE international conference on robotics and automation (ICRA), 1134-1141, 2018 | 776* | 2018 |
| Learning convolutional feature hierarchies for visual recognition K Kavukcuoglu, P Sermanet, YL Boureau, K Gregor, M Mathieu, Y Cun Advances in neural information processing systems 23, 2010 | 720 | 2010 |
| Convolutional Neural Networks Applied to House Numbers Digit Classification P Sermanet, S Chintala, Y LeCun 21st International Conference on Pattern Recognition (ICPR 2012), 3288-3291, 2012 | 677 | 2012 |
| Learning long‐range vision for autonomous off‐road driving R Hadsell, P Sermanet, J Ben, A Erkan, M Scoffier, K Kavukcuoglu, ... Journal of Field Robotics 26 (2), 120-144, 2009 | 435 | 2009 |
| Do as i can, not as i say: Grounding language in robotic affordances M Ahn, A Brohan, N Brown, Y Chebotar, O Cortes, B David, C Finn, ... arXiv preprint arXiv:2204.01691, 2022 | 286 | 2022 |
| Learning latent plans from play C Lynch, M Khansari, T Xiao, V Kumar, J Tompson, S Levine, P Sermanet Conference on robot learning, 1113-1132, 2020 | 245 | 2020 |
| Temporal cycle-consistency learning D Dwibedi, Y Aytar, J Tompson, P Sermanet, A Zisserman Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 230 | 2019 |
| With a little help from my friends: Nearest-neighbor contrastive learning of visual representations D Dwibedi, Y Aytar, J Tompson, P Sermanet, A Zisserman Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 221 | 2021 |
| Attention for fine-grained categorization P Sermanet, A Frome, E Real [ICLR 2015] International Conference on Learning Representations Workshop, 2014 | 187 | 2014 |
| Unsupervised Perceptual Rewards for Imitation Learning P Sermanet, K Xu, S Levine [RSS 2017] Robotics: Science and Systems + Deep Learning for Action and …, 2016 | 154 | 2016 |
| Language conditioned imitation learning over unstructured data C Lynch, P Sermanet Robotics: Science and Systems 2021, http://www.roboticsproceedings.org/rss17, 2020 | 142* | 2020 |
| Deep belief net learning in a long-range vision system for autonomous off-road driving R Hadsell, A Erkan, P Sermanet, M Scoffier, U Muller, Y LeCun 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2008 | 128 | 2008 |
| Inner monologue: Embodied reasoning through planning with language models W Huang, F Xia, T Xiao, H Chan, J Liang, P Florence, A Zeng, J Tompson, ... arXiv preprint arXiv:2207.05608, 2022 | 107 | 2022 |
| Learning Actionable Representations from Visual Observations D Dwibedi, J Tompson, C Lynch, P Sermanet [IROS 2018] International Conference on Intelligent Robots, 2018 | 84 | 2018 |
| Wasserstein dependency measure for representation learning S Ozair, C Lynch, Y Bengio, A Van den Oord, S Levine, P Sermanet Advances in Neural Information Processing Systems 32, 2019 | 83 | 2019 |
| Palm-e: An embodied multimodal language model D Driess, F Xia, MSM Sajjadi, C Lynch, A Chowdhery, B Ichter, A Wahid, ... arXiv preprint arXiv:2303.03378, 2023 | 79 | 2023 |
Yann LeCunChief AI Scientist at Facebook & Silver Professor at the Courant Institute, New York UniversityPotvrđena adresa e-pošte na cs.nyu.edu
