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Mathew Monfort
Mathew Monfort
Amazon AWS
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Cited by
Year
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
50182016
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
5912019
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
4382019
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
1902015
Robust covariate shift regression
X Chen, M Monfort, A Liu, BD Ziebart
Artificial Intelligence and Statistics, 1270-1279, 2016
802016
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
692021
Intent Prediction and Trajectory Forecasting via Predictive Inverse Linear-Quadratic Regulation.
M Monfort, A Liu, BD Ziebart
AAAI, 3672-3678, 2015
612015
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
522021
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
522016
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
392019
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
382016
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
362017
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
342015
& 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
28
Goal-Predictive Robotic Teleoperation from Noisy Sensors
C Schultz, S Gaurav, M Monfort, L Zhang, BD Ziebart
ICRA, 2017
252017
& 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
19
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
92020
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
92017
End to end learning for self-driving cars. CoRR (2016)
M Bojarski, D Del Testa, D Dworakowski, B Firner, B Flepp, P Goyal, ...
arXiv preprint arXiv:1604.07316, 2016
92016
et almbox. 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, 2016
92016
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