Mathew Monfort

26 papers A* 7A 3Journal 11Unranked 5

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	A Framework for Efficient Model Evaluation Through Stratification, Sampling, and Estimation. ECCV (88) Riccardo Fogliato, Pratik Patil, Mathew Monfort, Pietro Perona
2024	J	`jnl`	A Framework for Efficient Model Evaluation through Stratification, Sampling, and Estimation. CoRR Riccardo Fogliato, Pratik Patil, Mathew Monfort, Pietro Perona
2024	—	`conf`	Model ChangeLists: Characterizing Updates to ML Models. FAccT Sabri Eyuboglu, Karan Goel, Arjun Desai, Lingjiao Chen, Mathew Monfort, Christopher Ré, James Zou
2024	A*	`conf`	Precise Model Benchmarking with Only a Few Observations. EMNLP Riccardo Fogliato, Pratik Patil, Nil-Jana Akpinar, Mathew Monfort
2024	J	`jnl`	Precise Model Benchmarking with Only a Few Observations. CoRR Riccardo Fogliato, Pratik Patil, Nil-Jana Akpinar, Mathew Monfort
2022	J	`jnl`	Multi-Moments in Time: Learning and Interpreting Models for Multi-Action Video Understanding. IEEE Trans. Pattern Anal. Mach. Intell. Mathew Monfort, Bowen Pan, Kandan Ramakrishnan, Alex Andonian, Barry A. McNamara, Alex Lascelles, Quanfu Fan, Dan Gutfreund, Rogério Schmidt Feris, Aude Oliva
2021	A*	`conf`	Spoken Moments: Learning Joint Audio-Visual Representations From Video Descriptions. CVPR Mathew Monfort, SouYoung Jin, Alexander H. Liu, David Harwath, Rogério Feris, James R. Glass, Aude Oliva
2021	J	`jnl`	Spoken Moments: Learning Joint Audio-Visual Representations from Video Descriptions. CoRR Mathew Monfort, SouYoung Jin, Alexander H. Liu, David Harwath, Rogério Feris, James R. Glass, Aude Oliva
2020	J	`jnl`	Moments in Time Dataset: One Million Videos for Event Understanding. IEEE Trans. Pattern Anal. Mach. Intell. Mathew Monfort, Carl Vondrick, Aude Oliva, Alex Andonian, Bolei Zhou, Kandan Ramakrishnan, Sarah Adel Bargal, Tom Yan, Lisa M. Brown, Quanfu Fan, Dan Gutfreund
2020	J	`jnl`	We Have So Much In Common: Modeling Semantic Relational Set Abstractions in Videos. CoRR Alex Andonian, Camilo Fosco, Mathew Monfort, Allen Lee, Rogério Feris, Carl Vondrick, Aude Oliva
2020	—	`conf`	We Have So Much in Common: Modeling Semantic Relational Set Abstractions in Videos. ECCV (18) Alex Andonian, Camilo Fosco, Mathew Monfort, Allen Lee, Rogério Feris, Carl Vondrick, Aude Oliva
2019	—	`conf`	Identifying Interpretable Action Concepts in Deep Networks. CVPR Workshops Kandan Ramakrishnan, Mathew Monfort, Barry A. McNamara, Alex Lascelles, Dan Gutfreund, Rogério Schmidt Feris, Aude Oliva
2019	A*	`conf`	Multi-Agent Tensor Fusion for Contextual Trajectory Prediction. CVPR Tianyang Zhao, Yifei Xu, Mathew Monfort, Wongun Choi, Chris L. Baker, Yibiao Zhao, Yizhou Wang, Ying Nian Wu
2019	J	`jnl`	Multi-Agent Tensor Fusion for Contextual Trajectory Prediction. CoRR Tianyang Zhao, Yifei Xu, Mathew Monfort, Wongun Choi, Chris L. Baker, Yibiao Zhao, Yizhou Wang, Ying Nian Wu
2019	J	`jnl`	Multi-Moments in Time: Learning and Interpreting Models for Multi-Action Video Understanding. CoRR Mathew Monfort, Kandan Ramakrishnan, Alex Andonian, Barry A. McNamara, Alex Lascelles, Bowen Pan, Quanfu Fan, Dan Gutfreund, Rogério Schmidt Feris, Aude Oliva
2019	A*	`conf`	Reasoning About Human-Object Interactions Through Dual Attention Networks. ICCV Tete Xiao, Quanfu Fan, Danny Gutfreund, Mathew Monfort, Aude Oliva, Bolei Zhou
2019	J	`jnl`	Reasoning About Human-Object Interactions Through Dual Attention Networks. CoRR Tete Xiao, Quanfu Fan, Dan Gutfreund, Mathew Monfort, Aude Oliva, Bolei Zhou
2018	J	`jnl`	Moments in Time Dataset: one million videos for event understanding. CoRR Mathew Monfort, Bolei Zhou, Sarah Adel Bargal, Alex Andonian, Tom Yan, Kandan Ramakrishnan, Lisa M. Brown, Quanfu Fan, Dan Gutfreund, Carl Vondrick, Aude Oliva
2017	A	`conf`	Asynchronous Data Aggregation for Training End to End Visual Control Networks. AAMAS Mathew Monfort, Matthew Johnson, Aude Oliva, Katja Hofmann
2017	A*	`conf`	Goal-predictive robotic teleoperation from noisy sensors. ICRA Christopher Schultz, Sanket Gaurav, Mathew Monfort, Lingfei Zhang, Brian D. Ziebart
2016	A	`conf`	Adversarial Inverse Optimal Control for General Imitation Learning Losses and Embodiment Transfer. UAI Xiangli Chen, Mathew Monfort, Brian D. Ziebart, Peter Carr
2016	J	`jnl`	End to End Learning for Self-Driving Cars. CoRR 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
2016	A	`conf`	Robust Covariate Shift Regression. AISTATS Xiangli Chen, Mathew Monfort, Anqi Liu, Brian D. Ziebart
2015	A*	`conf`	Graph-Based Inverse Optimal Control for Robot Manipulation. IJCAI Arunkumar Byravan, Mathew Monfort, Brian D. Ziebart, Byron Boots, Dieter Fox
2015	A*	`conf`	Intent Prediction and Trajectory Forecasting via Predictive Inverse Linear-Quadratic Regulation. AAAI Mathew Monfort, Anqi Liu, Brian D. Ziebart
2015	—	`conf`	Softstar: Heuristic-Guided Probabilistic Inference. NIPS Mathew Monfort, Brenden M. Lake, Brian D. Ziebart, Patrick Lucey, Joshua B. Tenenbaum