Paull, Liam

29 publications

TMLR 2025 GROOD: GRadient-Aware Out-of-Distribution Detection Mostafa ElAraby, Sabyasachi Sahoo, Yann Pequignot, Paul Novello, Liam Paull

NeurIPS 2025 OpenLex3D: A Tiered Benchmark for Open-Vocabulary 3D Scene Representations Christina Kassab, Sacha Morin, Martin Büchner, Matias Mattamala, Kumaraditya Gupta, Abhinav Valada, Liam Paull, Maurice Fallon

ICLR 2025 Safety Representations for Safer Policy Learning Kaustubh Mani, Vincent Mai, Charlie Gauthier, Annie S Chen, Samer B. Nashed, Liam Paull

CVPR 2025 Scenario Dreamer: Vectorized Latent Diffusion for Generating Driving Simulation Environments Luke Rowe, Roger Girgis, Anthony Gosselin, Liam Paull, Christopher Pal, Felix Heide

MLJ 2024 Correction to: Multi-Agent Reinforcement Learning for Fast-Timescale Demand Response of Residential Loads Vincent Mai, Philippe Maisonneuve, Tianyu Zhang, Hadi Nekoei, Liam Paull, Antoine Lesage-Landry

CoRL 2024 CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learning Luke Rowe, Roger Girgis, Anthony Gosselin, Bruno Carrez, Florian Golemo, Felix Heide, Liam Paull, Christopher Pal

ICLR 2024 Ghost on the Shell: An Expressive Representation of General 3D Shapes Zhen Liu, Yao Feng, Yuliang Xiu, Weiyang Liu, Liam Paull, Michael J. Black, Bernhard Schölkopf

MLJ 2024 Multi-Agent Reinforcement Learning for Fast-Timescale Demand Response of Residential Loads Vincent Mai, Philippe Maisonneuve, Tianyu Zhang, Hadi Nekoei, Liam Paull, Antoine Lesage-Landry

TMLR 2024 Rethinking Teacher-Student Curriculum Learning Through the Cooperative Mechanics of Experience Manfred Diaz, Liam Paull, Andrea Tacchetti

AAAI 2023 Estimating Regression Predictive Distributions with Sample Networks Ali Harakeh, Jordan Sir Kwang Hu, Naiqing Guan, Steven L. Waslander, Liam Paull

ICLR 2023 MeshDiffusion: Score-Based Generative 3D Mesh Modeling Zhen Liu, Yao Feng, Michael J. Black, Derek Nowrouzezahrai, Liam Paull, Weiyang Liu

NeurIPSW 2023 Rethinking Teacher-Student Curriculum Learning Under the Cooperative Mechanics of Experience Manfred Diaz, Liam Paull, Andrea Tacchetti

ICLR 2023 Robust and Controllable Object-Centric Learning Through Energy-Based Models Ruixiang Zhang, Tong Che, Boris Ivanovic, Renhao Wang, Marco Pavone, Yoshua Bengio, Liam Paull

CVPR 2023 Self-Supervised Image-to-Point Distillation via Semantically Tolerant Contrastive Loss Anas Mahmoud, Jordan S. K. Hu, Tianshu Kuai, Ali Harakeh, Liam Paull, Steven L. Waslander

ICLRW 2022 Generalization Games for Reinforcement Learning Manfred Diaz, Charlie Gauthier, Glen Berseth, Liam Paull

ICLR 2022 Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation Vincent Mai, Kaustubh Mani, Liam Paull

ECCV 2022 Structural Causal 3D Reconstruction Weiyang Liu, Zhen Liu, Liam Paull, Adrian Weller, Bernhard Schölkopf

NeurIPS 2021 Iterative Teaching by Label Synthesis Weiyang Liu, Zhen Liu, Hanchen Wang, Liam Paull, Bernhard Schölkopf, Adrian Weller

CVPR 2021 Orthogonal Over-Parameterized Training Weiyang Liu, Rongmei Lin, Zhen Liu, James M. Rehg, Liam Paull, Li Xiong, Le Song, Adrian Weller

CoRL 2021 Taskography: Evaluating Robot Task Planning over Large 3D Scene Graphs Christopher Agia, Krishna Murthy Jatavallabhula, Mohamed Khodeir, Ondrej Miksik, Vibhav Vineet, Mustafa Mukadam, Liam Paull, Florian Shkurti

ICLR 2021 gradSim: Differentiable Simulation for System Identification and Visuomotor Control J. Krishna Murthy, Miles Macklin, Florian Golemo, Vikram Voleti, Linda Petrini, Martin Weiss, Breandan Considine, Jérôme Parent-Lévesque, Kevin Xie, Kenny Erleben, Liam Paull, Florian Shkurti, Derek Nowrouzezahrai, Sanja Fidler

ICMLW 2020 La-MAML: Look-Ahead Meta Learning for Continual Learning Gunshi Gupta, Karmesh Yadav, Liam Paull

NeurIPS 2020 Look-Ahead Meta Learning for Continual Learning Gunshi Gupta, Karmesh Yadav, Liam Paull

ICML 2020 Perceptual Generative Autoencoders Zijun Zhang, Ruixiang Zhang, Zongpeng Li, Yoshua Bengio, Liam Paull

NeurIPS 2020 Your GAN Is Secretly an Energy-Based Model and You Should Use Discriminator Driven Latent Sampling Tong Che, Ruixiang Zhang, Jascha Sohl-Dickstein, Hugo Larochelle, Liam Paull, Yuan Cao, Yoshua Bengio

CoRL 2019 Active Domain Randomization Bhairav Mehta, Manfred Diaz, Florian Golemo, Christopher J. Pal, Liam Paull

NeurIPSW 2019 Kotlin∇: A Shape-Safe DSL for Differentiable Programming Breandan Considine, Michalis Famelis, Liam Paull

ICLRW 2019 Perceptual Generative Autoencoders Zijun Zhang, Ruixiang Zhang, Zongpeng Li, Yoshua Bengio, Liam Paull

CVPRW 2018 Geometric Consistency for Self-Supervised End-to-End Visual Odometry Ganesh Iyer, J. Krishna Murthy, Gunshi Gupta, K. Madhava Krishna, Liam Paull