Lavington, Jonathan Wilder

9 publications

ICML 2024 Nearest Neighbour Score Estimators for Diffusion Generative Models Matthew Niedoba, Dylan Green, Saeid Naderiparizi, Vasileios Lioutas, Jonathan Wilder Lavington, Xiaoxuan Liang, Yunpeng Liu, Ke Zhang, Setareh Dabiri, Adam Scibior, Berend Zwartsenberg, Frank Wood

TMLR 2023 Conditional Permutation Invariant Flows Berend Zwartsenberg, Adam Scibior, Matthew Niedoba, Vasileios Lioutas, Justice Sefas, Yunpeng Liu, Setareh Dabiri, Jonathan Wilder Lavington, Trevor Campbell, Frank Wood

ICLR 2023 Critic Sequential Monte Carlo Vasileios Lioutas, Jonathan Wilder Lavington, Justice Sefas, Matthew Niedoba, Yunpeng Liu, Berend Zwartsenberg, Setareh Dabiri, Frank Wood, Adam Scibior

ICLR 2023 Noise Is Not the Main Factor Behind the Gap Between SGD and Adam on Transformers, but Sign Descent Might Be Frederik Kunstner, Jacques Chen, Jonathan Wilder Lavington, Mark Schmidt

ICML 2023 Target-Based Surrogates for Stochastic Optimization Jonathan Wilder Lavington, Sharan Vaswani, Reza Babanezhad Harikandeh, Mark Schmidt, Nicolas Le Roux

CoLLAs 2022 Improved Policy Optimization for Online Imitation Learning Jonathan Wilder Lavington, Sharan Vaswani, Mark Schmidt

NeurIPSW 2022 Target-Based Surrogates for Stochastic Optimization Jonathan Wilder Lavington, Sharan Vaswani, Reza Babanezhad Harikandeh, Mark Schmidt, Nicolas Le Roux

NeurIPSW 2021 A Closer Look at Gradient Estimators with Reinforcement Learning as Inference Jonathan Wilder Lavington, Michael Teng, Mark Schmidt, Frank Wood

NeurIPSW 2021 An Empirical Study of Non-Uniform Sampling in Off-Policy Reinforcement Learning for Continuous Control Nicholas Ioannidis, Jonathan Wilder Lavington, Mark Schmidt