Jackson, Matthew Thomas

9 publications

NeurIPS 2025 A Clean Slate for Offline Reinforcement Learning Matthew Thomas Jackson, Uljad Berdica, Jarek Luca Liesen, Shimon Whiteson, Jakob Nicolaus Foerster

NeurIPS 2025 Imagined Autocurricula Ahmet H. Güzel, Matthew Thomas Jackson, Jarek Luca Liesen, Tim Rocktäschel, Jakob Nicolaus Foerster, Ilija Bogunovic, Jack Parker-Holder

ICMLW 2024 Can Learned Optimization Make Reinforcement Learning Less Difficult? Alexander D. Goldie, Chris Lu, Matthew Thomas Jackson, Shimon Whiteson, Jakob Nicolaus Foerster

ICML 2024 Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning Michael Matthews, Michael Beukman, Benjamin Ellis, Mikayel Samvelyan, Matthew Thomas Jackson, Samuel Coward, Jakob Nicolaus Foerster

ICLR 2024 Discovering Temporally-Aware Reinforcement Learning Algorithms Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster

ICMLW 2024 Jafar: An Open-Source Genie Reimplemention in JAX Timon Willi, Matthew Thomas Jackson, Jakob Nicolaus Foerster

ICML 2024 Position: Near to Mid-Term Risks and Opportunities of Open-Source Generative AI Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schroeder De Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Botos Csaba, Fabro Steibel, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Thomas Jackson, Paul Rottger, Philip Torr, Trevor Darrell, Yong Suk Lee, Jakob Nicolaus Foerster

NeurIPSW 2023 Discovering Temporally-Aware Reinforcement Learning Algorithms Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster

CoRL 2022 Hypernetworks in Meta-Reinforcement Learning Jacob Beck, Matthew Thomas Jackson, Risto Vuorio, Shimon Whiteson