Mathew Monfort

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 20

Top Topics

Trecvid Multimedia Event Detection

Optimal Control

Top Venues

IEEE Trans. Pattern Anal. Mach. Intell.

Publications

Riccardo Fogliato, Pratik Patil, Mathew Monfort, Pietro Perona
A Framework for Efficient Model Evaluation through Stratification, Sampling, and Estimation. CoRR (2024)
Sabri Eyuboglu, Karan Goel, Arjun D. Desai, Lingjiao Chen, Mathew Monfort, Christopher Ré, James Zou
Model ChangeLists: Characterizing Updates to ML Models. FAccT (2024)
Mathew Monfort, Bowen Pan, Kandan Ramakrishnan, Alex Andonian, Barry A. McNamara, Alex Lascelles, Quanfu Fan, Dan Gutfreund, Rogério Schmidt Feris, Aude Oliva
Multi-Moments in Time: Learning and Interpreting Models for Multi-Action Video Understanding. IEEE Trans. Pattern Anal. Mach. Intell. 44 (12) (2022)
Mathew Monfort, SouYoung Jin, Alexander H. Liu, David Harwath, Rogério Feris, James R. Glass, Aude Oliva
Spoken Moments: Learning Joint Audio-Visual Representations From Video Descriptions. CVPR (2021)
Mathew Monfort, SouYoung Jin, Alexander H. Liu, David Harwath, Rogério Feris, James R. Glass, Aude Oliva
Spoken Moments: Learning Joint Audio-Visual Representations from Video Descriptions. CoRR (2021)
Alex Andonian, Camilo Fosco, Mathew Monfort, Allen Lee, Rogério Feris, Carl Vondrick, Aude Oliva
We Have So Much In Common: Modeling Semantic Relational Set Abstractions in Videos. CoRR (2020)
Alex Andonian, Camilo Fosco, Mathew Monfort, Allen Lee, Rogério Feris, Carl Vondrick, Aude Oliva
We Have So Much in Common: Modeling Semantic Relational Set Abstractions in Videos. ECCV (18) (2020)
Mathew Monfort, Carl Vondrick, Aude Oliva, Alex Andonian, Bolei Zhou, Kandan Ramakrishnan, Sarah Adel Bargal, Tom Yan, Lisa M. Brown, Quanfu Fan, Dan Gutfreund
Moments in Time Dataset: One Million Videos for Event Understanding. IEEE Trans. Pattern Anal. Mach. Intell. 42 (2) (2020)
Tete Xiao, Quanfu Fan, Dan Gutfreund, Mathew Monfort, Aude Oliva, Bolei Zhou
Reasoning About Human-Object Interactions Through Dual Attention Networks. CoRR (2019)
Mathew Monfort, Kandan Ramakrishnan, Alex Andonian, Barry A. McNamara, Alex Lascelles, Bowen Pan, Quanfu Fan, Dan Gutfreund, Rogério Schmidt Feris, Aude Oliva
Multi-Moments in Time: Learning and Interpreting Models for Multi-Action Video Understanding. CoRR (2019)
Kandan Ramakrishnan, Mathew Monfort, Barry A. McNamara, Alex Lascelles, Dan Gutfreund, Rogério Schmidt Feris, Aude Oliva
Identifying Interpretable Action Concepts in Deep Networks. CVPR Workshops (2019)
Tianyang Zhao, Yifei Xu, Mathew Monfort, Wongun Choi, Chris L. Baker, Yibiao Zhao, Yizhou Wang, Ying Nian Wu
Multi-Agent Tensor Fusion for Contextual Trajectory Prediction. CoRR (2019)
Tianyang Zhao, Yifei Xu, Mathew Monfort, Wongun Choi, Chris L. Baker, Yibiao Zhao, Yizhou Wang, Ying Nian Wu
Multi-Agent Tensor Fusion for Contextual Trajectory Prediction. CVPR (2019)
Tete Xiao, Quanfu Fan, Danny Gutfreund, Mathew Monfort, Aude Oliva, Bolei Zhou
Reasoning About Human-Object Interactions Through Dual Attention Networks. ICCV (2019)
Mathew Monfort, Bolei Zhou, Sarah Adel Bargal, Alex Andonian, Tom Yan, Kandan Ramakrishnan, Lisa M. Brown, Quanfu Fan, Dan Gutfreund, Carl Vondrick, Aude Oliva
Moments in Time Dataset: one million videos for event understanding. CoRR (2018)
Christopher Schultz, Sanket Gaurav, Mathew Monfort, Lingfei Zhang, Brian D. Ziebart
Goal-predictive robotic teleoperation from noisy sensors. ICRA (2017)
Mathew Monfort, Matthew Johnson, Aude Oliva, Katja Hofmann
Asynchronous Data Aggregation for Training End to End Visual Control Networks. AAMAS (2017)
Xiangli Chen, Mathew Monfort, Anqi Liu, Brian D. Ziebart
Robust Covariate Shift Regression. AISTATS (2016)
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D. Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, Xin Zhang, Jake Zhao, Karol Zieba
End to End Learning for Self-Driving Cars. CoRR (2016)
Xiangli Chen, Mathew Monfort, Brian D. Ziebart, Peter Carr
Adversarial Inverse Optimal Control for General Imitation Learning Losses and Embodiment Transfer. UAI (2016)
Mathew Monfort, Anqi Liu, Brian D. Ziebart
Intent Prediction and Trajectory Forecasting via Predictive Inverse Linear-Quadratic Regulation. AAAI (2015)
Mathew Monfort, Brenden M. Lake, Brian D. Ziebart, Patrick Lucey, Joshua B. Tenenbaum
Softstar: Heuristic-Guided Probabilistic Inference. NIPS (2015)
Arunkumar Byravan, Mathew Monfort, Brian D. Ziebart, Byron Boots, Dieter Fox
Graph-Based Inverse Optimal Control for Robot Manipulation. IJCAI (2015)