Publications

Conference and journal papers, workshop papers, preprints, and theses. Author lists follow the published order. A continuously updated list lives on Google Scholar.

2024

Taking Advantage of Common Assumptions in Policy Optimization and Reinforcement Learning

J. Wilder Lavington

PhD Thesis 2024 PhD Thesis, University of British Columbia

• Paper
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Nearest Neighbour Score Estimators for Diffusion Generative Models

Matthew Niedoba, Dylan Green, Saeid Naderiparizi, Vasileios Lioutas, J. Wilder Lavington, Xiaoxuan Liang, Yunpeng Liu, Ke Zhang, Setareh Dabiri, Adam Scibior, Berend Zwartsenberg, Frank Wood

ICML 2024 International Conference on Machine Learning (ICML)

• arXiv
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TorchDriveEnv: A Reinforcement Learning Benchmark for Autonomous Driving with Reactive, Realistic, and Diverse Non-Playable Characters

J. Wilder Lavington, Ke Zhang, Vasileios Lioutas, Matthew Niedoba, Yunpeng Liu, Dylan Green, Saeid Naderiparizi, Xiaoxuan Liang, Setareh Dabiri, Adam Scibior, Berend Zwartsenberg, Frank Wood

arXiv 2024 arXiv preprint

• arXiv
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Semantically Consistent Video Inpainting with Conditional Diffusion Models

Dylan Green, William Harvey, Saeid Naderiparizi, Matthew Niedoba, Yunpeng Liu, Xiaoxuan Liang, J. Wilder Lavington, Ke Zhang, Vasileios Lioutas, Setareh Dabiri, Adam Scibior, Berend Zwartsenberg, Frank Wood

arXiv 2024 arXiv preprint

• arXiv
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• BibTeX

2023

Analyzing and Improving Greedy 2-Coordinate Updates for Equality-Constrained Optimization via Steepest Descent in the 1-Norm

Amrutha Varshini Ramesh, Aaron Mishkin, Mark Schmidt, Yihan Zhou, J. Wilder Lavington, Jennifer She

arXiv 2023 arXiv preprint

• arXiv
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Realistically Distributing Object Placements in Synthetic Training Data Improves the Performance of Vision-Based Object Detection Models

Setareh Dabiri, Vasileios Lioutas, Berend Zwartsenberg, Yunpeng Liu, Matthew Niedoba, Xiaoxuan Liang, Dylan Green, Justice Sefas, J. Wilder Lavington, Frank Wood, Adam Scibior

CVPR Workshop 2023 CVPR Workshop

• arXiv
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Video Killed the HD-Map: Predicting Multi-Agent Behavior Directly From Aerial Images

Yunpeng Liu, Vasileios Lioutas, J. Wilder Lavington, Matthew Niedoba, Justice Sefas, Setareh Dabiri, Dylan Green, Xiaoxuan Liang, Berend Zwartsenberg, Adam Scibior, Frank Wood

IEEE ITSC 2023 IEEE International Conference on Intelligent Transportation Systems (ITSC)

• arXiv
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Conditional Permutation Invariant Flows

Berend Zwartsenberg, Adam Scibior, Matthew Niedoba, Vasileios Lioutas, Justice Sefas, Yunpeng Liu, Setareh Dabiri, J. Wilder Lavington, Trevor Campbell, Frank Wood

TMLR 2023 Transactions on Machine Learning Research (TMLR)

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A Diffusion-Model of Joint Interactive Navigation

Matthew Niedoba, J. Wilder Lavington, Yunpeng Liu, Vasileios Lioutas, Justice Sefas, Xiaoxuan Liang, Dylan Green, Setareh Dabiri, Berend Zwartsenberg, Adam Scibior, Frank Wood

NeurIPS 2023 Advances in Neural Information Processing Systems (NeurIPS)

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Noise Is Not the Main Factor Behind the Gap Between SGD and Adam on Transformers, But Sign Descent Might Be

Frederik Kunstner, Jacques Chen, J. Wilder Lavington, Mark Schmidt

ICLR 2023 International Conference on Learning Representations (ICLR)

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Target-Based Surrogates for Stochastic Optimization

J. Wilder Lavington, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Nicolas Le Roux

ICML 2023 International Conference on Machine Learning (ICML)

• PDF
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• BibTeX

Critic Sequential Monte Carlo

Vasileios Lioutas, J. Wilder Lavington, Justice Sefas, Matthew Niedoba, Yunpeng Liu, Berend Zwartsenberg, Setareh Dabiri, Frank Wood, Adam Scibior

ICLR 2023 International Conference on Learning Representations (ICLR)

• Paper
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2022

Vehicle Type Specific Waypoint Generation

Yunpeng Liu, J. Wilder Lavington, Adam Scibior, Frank Wood

IROS 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Improved Policy Optimization for Online Imitation Learning

J. Wilder Lavington, Sharan Vaswani, Mark Schmidt

CoLLAs 2022 Conference on Lifelong Learning Agents (CoLLAs)

• PDF
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2021

A Closer Look at Gradient Estimators with Reinforcement Learning as Inference

J. Wilder Lavington, Michael Teng, Mark Schmidt, Frank Wood

NeurIPS Workshop 2021 Deep RL Workshop, NeurIPS

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Robust Asymmetric Learning in POMDPs

Andrew Warrington, J. Wilder Lavington, Adam Scibior, Mark Schmidt, Frank Wood

ICML 2021 International Conference on Machine Learning (ICML)

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An Empirical Study of Non-Uniform Sampling in Off-Policy Reinforcement Learning for Continuous Control

Nicholas Ioannidis, J. Wilder Lavington, Mark Schmidt

NeurIPS Workshop 2021 Deep RL Workshop, NeurIPS

• Paper
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2018

A Probabilistic Modeling Approach to CRISPR-Cas9

J. Wilder Lavington

MSc Thesis 2018 MSc Thesis, University of Colorado Boulder

• Paper
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• BibTeX