Deep Convolutional Inverse Graphics Network. - Tejas D. Kulkarni; William F. Whitney; Pushmeet Kohli; Joshua B. Tenenbaum (NIPS, 2015)

Disentangled Representations in Neural Models. - William Whitney 001 (CoRR, 2016)

Understanding Visual Concepts with Continuation Learning. - William F. Whitney; Michael Chang 003; Tejas D. Kulkarni; Joshua B. Tenenbaum (CoRR, 2016)

Beating the World's Best at Super Smash Bros. with Deep Reinforcement Learning. - Vlad Firoiu; William F. Whitney; Joshua B. Tenenbaum (CoRR, 2017)

Model-Based Planning in Discrete Action Spaces. - Mikael Henaff; William F. Whitney; Yann LeCun (CoRR, 2017)

Disentangling Video with Independent Prediction. - William F. Whitney; Rob Fergus (CoRR, 2019)

Dynamics-Aware Embeddings. - William F. Whitney; Rajat Agarwal; Kyunghyun Cho; Abhinav Gupta 001 (ICLR, 2020)

Overfitting and Optimization in Offline Policy Learning. - David Brandfonbrener; William F. Whitney; Rajesh Ranganath; Joan Bruna (CoRR, 2020)

Evaluating representations by the complexity of learning low-loss predictors. - William F. Whitney; Min Jae Song; David Brandfonbrener; Jaan Altosaar; Kyunghyun Cho (CoRR, 2020)

Offline Contextual Bandits with Overparameterized Models. - David Brandfonbrener; William F. Whitney; Rajesh Ranganath; Joan Bruna (ICML, 2021)

Offline RL Without Off-Policy Evaluation. - David Brandfonbrener; Will Whitney; Rajesh Ranganath; Joan Bruna (NeurIPS, 2021)

Rethinking Exploration for Sample-Efficient Policy Learning. - William F. Whitney; Michael Bloesch; Jost Tobias Springenberg; Abbas Abdolmaleki; Martin A. Riedmiller (CoRR, 2021)

Quantile Filtered Imitation Learning. - David Brandfonbrener; William F. Whitney; Rajesh Ranganath; Joan Bruna (CoRR, 2021)

Techniques for Sample-Efficient Reinforcement Learning. - William F. Whitney (2021)

The Challenges of Exploration for Offline Reinforcement Learning. - Nathan Lambert 001; Markus Wulfmeier; William F. Whitney; Arunkumar Byravan; Michael Bloesch; Vibhavari Dasagi; Tim Hertweck; Martin A. Riedmiller (CoRR, 2022)

Learning rigid dynamics with face interaction graph networks. - Kelsey R. Allen; Yulia Rubanova; Tatiana Lopez-Guevara; William Whitney 001; Alvaro Sanchez-Gonzalez; Peter W. Battaglia; Tobias Pfaff (ICLR, 2023)

Equivariant Data Augmentation for Generalization in Offline Reinforcement Learning. - Cristina Pinneri; Sarah Bechtle; Markus Wulfmeier; Arunkumar Byravan; Jingwei Zhang 001; William F. Whitney; Martin A. Riedmiller (CoRR, 2023)

Modeling the Real World with High-Density Visual Particle Dynamics. - William F. Whitney; Jake Varley; Deepali Jain; Krzysztof Marcin Choromanski; Sumeet Singh; Vikas Sindhwani (CoRL, 2024)

Learning 3D Particle-based Simulators from RGB-D Videos. - William F. Whitney; Tatiana Lopez-Guevara; Tobias Pfaff; Yulia Rubanova; Thomas Kipf; Kim Stachenfeld; Kelsey R. Allen (ICLR, 2024)

Learning rigid-body simulators over implicit shapes for large-scale scenes and vision. - Yulia Rubanova; Tatiana Lopez-Guevara; Kelsey R. Allen; Will Whitney; Kimberly L. Stachenfeld; Tobias Pfaff (NeurIPS, 2024)

Scaling Face Interaction Graph Networks to Real World Scenes. - Tatiana Lopez-Guevara; Yulia Rubanova; William F. Whitney; Tobias Pfaff; Kimberly L. Stachenfeld; Kelsey R. Allen (CoRR, 2024)

Modeling the Real World with High-Density Visual Particle Dynamics. - William F. Whitney; Jacob Varley; Deepali Jain; Krzysztof Choromanski; Sumeet Singh; Vikas Sindhwani (CoRR, 2024)

Neural rendering enables dynamic tomography. - Ivan Grega; William F. Whitney; Vikram S. Deshpande (CoRR, 2024)

Linear Transformer Topological Masking with Graph Random Features. - Isaac Reid; Kumar Avinava Dubey; Deepali Jain; William F. Whitney; Amr Ahmed 001; Joshua Ainslie; Alex Bewley; Mithun George Jacob; Aranyak Mehta; David Rendleman; Connor Schenck; Richard E. Turner; et al. (ICLR, 2025)

Value from Observations: Towards Large-Scale Imitation Learning via Self-Improvement. - Michael Bloesch; Markus Wulfmeier; Philemon Brakel; Todor Davchev; Martina Zambelli; Jost Tobias Springenberg; Abbas Abdolmaleki; William F. Whitney; Nicolas Heess; Roland Hafner; Martin A. Riedmiller (CoRR, 2025)