Eaton, Eric

45 publications

ICLR 2025 Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model Long Le, Jason Xie, William Liang, Hung-Ju Wang, Yue Yang, Yecheng Jason Ma, Kyle Vedder, Arjun Krishna, Dinesh Jayaraman, Eric Eaton

AAAI 2025 Assessing Modality Bias in Video Question Answering Benchmarks with Multimodal Large Language Models Jean Park, Kuk Jin Jang, Basam Alasaly, Sriharsha Mopidevi, Andrew Zolensky, Eric Eaton, Insup Lee, Kevin B. Johnson

WACV 2025 Disentangling Spatio-Temporal Knowledge for Weakly Supervised Object Detection and Segmentation in Surgical Video Guiqiu Liao, Matjaz Jogan, Sai Koushik, Eric Eaton, Daniel A. Hashimoto

NeurIPS 2025 FORLA: Federated Object-Centric Representation Learning with Slot Attention Guiqiu Liao, Matjaz Jogan, Eric Eaton, Daniel A Hashimoto

ICML 2025 Intersectional Fairness in Reinforcement Learning with Large State and Constraint Spaces Eric Eaton, Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta, Jessica Sorrell

ICLR 2025 MAD-TD: Model-Augmented Data Stabilizes High Update Ratio RL Claas A Voelcker, Marcel Hussing, Eric Eaton, Amir-massoud Farahmand, Igor Gilitschenski

ICLR 2025 Neural Eulerian Scene Flow Fields Kyle Vedder, Neehar Peri, Ishan Khatri, Siyi Li, Eric Eaton, Mehmet Kemal Kocamaz, Yue Wang, Zhiding Yu, Deva Ramanan, Joachim Pehserl

AAAI 2024 Artificial Intelligence in the CS2023 Undergraduate Computer Science Curriculum: Rationale and Challenges Eric Eaton, Susan L. Epstein

ICLR 2024 ZeroFlow: Scalable Scene Flow via Distillation Kyle Vedder, Neehar Peri, Nathaniel Eliot Chodosh, Ishan Khatri, Eric Eaton, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays

JMLR 2023 Gap Minimization for Knowledge Sharing and Transfer Boyu Wang, Jorge A. Mendez, Changjian Shui, Fan Zhou, Di Wu, Gezheng Xu, Christian Gagné, Eric Eaton

TMLR 2023 How to Reuse and Compose Knowledge for a Lifetime of Tasks: A Survey on Continual Learning and Functional Composition Jorge A Mendez, Eric Eaton

CoLLAs 2023 Prospective Learning: Principled Extrapolation to the Future Ashwin De Silva, Rahul Ramesh, Lyle Ungar, Marshall Hussain Shuler, Noah J. Cowan, Michael Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu Timothy Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein

NeurIPS 2023 Replicable Reinforcement Learning Eric Eaton, Marcel Hussing, Michael J. Kearns, Jessica Sorrell

CoLLAs 2022 CompoSuite: A Compositional Reinforcement Learning Benchmark Jorge A. Mendez, Marcel Hussing, Meghna Gummadi, Eric Eaton

ICLR 2022 Modular Lifelong Reinforcement Learning via Neural Composition Jorge A Mendez, Harm van Seijen, Eric Eaton

CoLLAs 2022 SHELS: Exclusive Feature Sets for Novelty Detection and Continual Learning Without Class Boundaries Meghna Gummadi, David Kent, Jorge A. Mendez, Eric Eaton

ICLR 2021 Lifelong Learning of Compositional Structures Jorge A Mendez, Eric Eaton

ICML 2021 Sharing Less Is More: Lifelong Learning in Deep Networks with Selective Layer Transfer Seungwon Lee, Sima Behpour, Eric Eaton

ICMLW 2020 Lifelong Learning of Factored Policies via Policy Gradients Jorge A Mendez, Eric Eaton

NeurIPS 2020 Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting Jorge Mendez, Boyu Wang, Eric Eaton

ICMLW 2020 Sharing Less Is More: Lifelong Learning in Deep Networks with Selective Layer Transfer Seungwon Lee, Sima Behpour, Eric Eaton

JAIR 2020 Using Task Descriptions in Lifelong Machine Learning for Improved Performance and Zero-Shot Transfer Mohammad Rostami, David Isele, Eric Eaton

AAAI 2019 A Lightweight Approach to Academic Research Group Management Using Online Tools: Spend More Time on Research and Less on Management Eric Eaton

IJCAI 2019 Learning Shared Knowledge for Deep Lifelong Learning Using Deconvolutional Networks Seungwon Lee, James Stokes, Eric Eaton

CVPRW 2019 SAR Image Classification Using Few-Shot Cross-Domain Transfer Learning Mohammad Rostami, Soheil Kolouri, Eric Eaton, Kyungnam Kim

NeurIPS 2019 Transfer Learning via Minimizing the Performance Gap Between Domains Boyu Wang, Jorge Mendez, Mingbo Cai, Eric Eaton

NeurIPS 2018 Lifelong Inverse Reinforcement Learning Jorge Mendez, Shashank Shivkumar, Eric Eaton

AAAI 2018 Lifelong Learning Networks: Beyond Single Agent Lifelong Learning Mohammad Rostami, Eric Eaton

ECML-PKDD 2017 Lifelong Learning with Gaussian Processes Christopher Clingerman, Eric Eaton

IJCAI 2016 Using Task Features for Zero-Shot Knowledge Transfer in Lifelong Learning David Isele, Mohammad Rostami, Eric Eaton

IJCAI 2015 Autonomous Cross-Domain Knowledge Transfer in Lifelong Policy Gradient Reinforcement Learning Haitham Bou-Ammar, Eric Eaton, José-Marcio Luna, Paul Ruvolo

ICML 2015 Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret Haitham Bou Ammar, Rasul Tutunov, Eric Eaton

AAAI 2015 Unsupervised Cross-Domain Transfer in Policy Gradient Reinforcement Learning via Manifold Alignment Haitham Bou-Ammar, Eric Eaton, Paul Ruvolo, Matthew E. Taylor

AAAI 2014 Online Multi-Task Gradient Temporal-Difference Learning Vishnu Purushothaman Sreenivasan, Haitham Bou-Ammar, Eric Eaton

ICML 2014 Online Multi-Task Learning for Policy Gradient Methods Haitham Bou Ammar, Eric Eaton, Paul Ruvolo, Matthew Taylor

AAAI 2014 Online Multi-Task Learning via Sparse Dictionary Optimization Paul Ruvolo, Eric Eaton

AAAI 2013 Active Task Selection for Lifelong Machine Learning Paul Ruvolo, Eric Eaton

ICML 2013 ELLA: An Efficient Lifelong Learning Algorithm Paul Ruvolo, Eric Eaton

AAAI 2012 A Spin-Glass Model for Semi-Supervised Community Detection Eric Eaton, Rachael A. Mansbach

AAAI 2011 Selective Transfer Between Learning Tasks Using Task-Based Boosting Eric Eaton, Marie desJardins

AAAI 2010 Interactive Learning Using Manifold Geometry Eric Eaton, Gary Holness, Daniel McFarlane

ECML-PKDD 2008 Modeling Transfer Relationships Between Learning Tasks for Improved Inductive Transfer Eric Eaton, Marie desJardins, Terran Lane

AAAI 2007 Using Multiresolution Learning for Transfer in Image Classification Eric Eaton, Marie desJardins, John Stevenson

ICML 2006 Learning User Preferences for Sets of Objects Marie desJardins, Eric Eaton, Kiri Wagstaff

AAAI 2006 Multi-Resolution Learning for Knowledge Transfer Eric Eaton