| End to end learning for self-driving cars M Bojarski, D Del Testa, D Dworakowski, B Firner, B Flepp, P Goyal, ... arXiv preprint arXiv:1604.07316, 2016 | 4657 | 2016 |
| Moments in time dataset: one million videos for event understanding M Monfort, A Andonian, B Zhou, K Ramakrishnan, SA Bargal, T Yan, ... IEEE transactions on pattern analysis and machine intelligence 42 (2), 502-508, 2019 | 540 | 2019 |
| Multi-agent tensor fusion for contextual trajectory prediction T Zhao, Y Xu, M Monfort, W Choi, C Baker, Y Zhao, Y Wang, YN Wu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 401 | 2019 |
| quality vs quantity: Improved shot prediction in soccer using strategic features from spatiotemporal data P Lucey, A Bialkowski, M Monfort, P Carr, I Matthews MIT, 2015 | 185 | 2015 |
| Robust covariate shift regression X Chen, M Monfort, A Liu, BD Ziebart Artificial Intelligence and Statistics, 1270-1279, 2016 | 71 | 2016 |
| Intent Prediction and Trajectory Forecasting via Predictive Inverse Linear-Quadratic Regulation. M Monfort, A Liu, BD Ziebart AAAI, 3672-3678, 2015 | 60 | 2015 |
| Multi-moments in time: Learning and interpreting models for multi-action video understanding M Monfort, B Pan, K Ramakrishnan, A Andonian, BA McNamara, ... IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 59 | 2021 |
| Spoken Moments: Learning Joint Audio-Visual Representations from Video Descriptions M Monfort, SY Jin, A Liu, D Harwath, R Feris, J Glass, A Oliva CVPR, 2021 | 45 | 2021 |
| End to end learning for self-driving cars B Mariusz, TD Del, D Daniel, F Bernhard, F Beat, G Prasoon arXiv preprint arXiv:1604.07316 1, 2016 | 44 | 2016 |
| End to end learning for self-driving cars. CoRR abs/1604.07316 (2016) M Bojarski, D Del Testa, D Dworakowski, B Firner, B Flepp, P Goyal, ... arXiv preprint arXiv:1604.07316, 2016 | 41 | 2016 |
| Reasoning about human-object interactions through dual attention networks T Xiao, Q Fan, D Gutfreund, M Monfort, A Oliva, B Zhou Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 39 | 2019 |
| A Deep Learning Approach to Identifying Shock Locations in Turbulent Combustion Tensor Fields M Monfort, T Luciani, J Komperda, B Ziebart, F Mashayek, GE Marai Modeling, Analysis, and Visualization of Anisotropy, 2017 | 34 | 2017 |
| End-to-end deep learning for self-driving cars M Bojarski, B Firner, B Flepp, L Jackel, U Muller, K Zieba, D Testa arXiv preprint arXiv:1604.07316, 2016 | 34 | 2016 |
| Graph-based inverse optimal control for robot manipulation A Byravan, M Monfort, B Ziebart, B Boots, D Fox Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015 | 32 | 2015 |
| Goal-Predictive Robotic Teleoperation from Noisy Sensors C Schultz, S Gaurav, M Monfort, L Zhang, BD Ziebart ICRA, 2017 | 25 | 2017 |
| & Zhang, X.(2016). End to end learning for self-driving cars M Bojarski, D Del Testa, D Dworakowski, B Firner, B Flepp, P Goyal arXiv preprint arXiv:1604.07316, 0 | 24 | |
| & Zieba, K.(2016). End to end learning for self-driving cars M Bojarski, D Del Testa, D Dworakowski, B Firner, B Flepp, P Goyal arXiv preprint arXiv:1604.07316, 0 | 16 | |
| End to end learning for self-driving cars. arXiv e-prints M Bojarski, D Del Testa, D Dworakowski, B Firner, B Flepp, P Goyal, ... arXiv preprint arXiv:1604.07316, 2016 | 11 | 2016 |
| We have so much in common: Modeling semantic relational set abstractions in videos A Andonian, C Fosco, M Monfort, A Lee, R Feris, C Vondrick, A Oliva Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 9 | 2020 |
| Asynchronous data aggregation for training end to end visual control networks M Monfort, M Johnson, A Oliva, K Hofmann Proceedings of the 16th Conference on Autonomous Agents and MultiAgent …, 2017 | 9 | 2017 |
Aude OlivaSenior Research Scientist, CSAIL, MIT Director MIT-IBM Lab, MIT College Director IndustryVerified email at mit.edu
