Midgley, Laurence Illing

6 publications

TMLR 2025 Efficient and Unbiased Sampling from Boltzmann Distributions via Variance-Tuned Diffusion Models Fengzhe Zhang, Laurence Illing Midgley, José Miguel Hernández-Lobato

ICLR 2024 Jumanji: A Diverse Suite of Scalable Reinforcement Learning Environments in JAX Clément Bonnet, Daniel Luo, Donal John Byrne, Shikha Surana, Sasha Abramowitz, Paul Duckworth, Vincent Coyette, Laurence Illing Midgley, Elshadai Tegegn, Tristan Kalloniatis, Omayma Mahjoub, Matthew Macfarlane, Andries Petrus Smit, Nathan Grinsztajn, Raphael Boige, Cemlyn Neil Waters, Mohamed Ali Ali Mimouni, Ulrich Armel Mbou Sob, Ruan John de Kock, Siddarth Singh, Daniel Furelos-Blanco, Victor Le, Arnu Pretorius, Alexandre Laterre

ICLR 2023 Flow Annealed Importance Sampling Bootstrap Laurence Illing Midgley, Vincent Stimper, Gregor N. C. Simm, Bernhard Schölkopf, José Miguel Hernández-Lobato

NeurIPSW 2023 SE(3) Equivariant Augmented Coupling Flows Laurence Illing Midgley, Vincent Stimper, Javier Antoran, Emile Mathieu, Bernhard Schölkopf, José Miguel Hernández-Lobato

NeurIPSW 2022 Debiasing Meta-Gradient Reinforcement Learning by Learning the Outer Value Function Clément Bonnet, Laurence Illing Midgley, Alexandre Laterre

NeurIPSW 2022 Flow Annealed Importance Sampling Bootstrap Laurence Illing Midgley, Vincent Stimper, Gregor N. C. Simm, Bernhard Schölkopf, José Miguel Hernández-Lobato