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

Multi-Modal Fusion by Meta-Initialization. - Matthew Thomas Jackson; Shreshth A. Malik; Michael T. Matthews; Yousuf Mohamed-Ahmed (CoRR, 2022)

Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design. - Matthew Thomas Jackson; Minqi Jiang; Jack Parker-Holder; Risto Vuorio; Chris Lu 001; Gregory Farquhar; Shimon Whiteson; Jakob N. Foerster (NeurIPS, 2023)

Discovering Temporally-Aware Reinforcement Learning Algorithms. - Matthew Thomas Jackson; Chris Lu 001; Louis Kirsch; Robert Tjarko Lange; Shimon Whiteson; Jakob Nicolaus Foerster (ICLR, 2024)

Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI. - Francisco Eiras; Aleksandar Petrov; Bertie Vidgen; Christian Schröder de Witt; Fabio Pizzati; Katherine Elkins; Supratik Mukhopadhyay; Adel Bibi; Botos Csaba; Fabro Steibel; Fazl Barez; Genevieve Smith; et al. (ICML, 2024)

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

Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps. - Benjamin Ellis; Matthew Thomas Jackson; Andrei Lupu; Alexander David Goldie; Mattie Fellows; Shimon Whiteson; Jakob N. Foerster (NeurIPS, 2024)

Can Learned Optimization Make Reinforcement Learning Less Difficult? - Alexander David Goldie; Chris Lu 001; Matthew Thomas Jackson; Shimon Whiteson; Jakob N. Foerster (NeurIPS, 2024)

SplAgger: Split Aggregation for Meta-Reinforcement Learning. - Jacob Beck; Matthew Thomas Jackson; Risto Vuorio; Zheng Xiong; Shimon Whiteson (RLJ, 2024)

Policy-Guided Diffusion. - Matthew Thomas Jackson; Michael T. Matthews; Cong Lu; Benjamin Ellis; Shimon Whiteson; Jakob Nicolaus Foerster (RLJ, 2024)

Reinforcement Learning Controllers for Soft Robots Using Learned Environments. - Uljad Berdica; Matthew Thomas Jackson; Niccolò Enrico Veronese; Jakob N. Foerster; Perla Maiolino (RoboSoft, 2024)

Near to Mid-term Risks and Opportunities of Open Source Generative AI. - Francisco Eiras; Aleksandar Petrov; Bertie Vidgen; Christian Schröder de Witt; Fabio Pizzati; Katherine Elkins; Supratik Mukhopadhyay; Adel Bibi; Botos Csaba; Fabro Steibel; Fazl Barez; Genevieve Smith; et al. (CoRR, 2024)

Risks and Opportunities of Open-Source Generative AI. - Francisco Eiras; Aleksandar Petrov; Bertie Vidgen; Christian Schröder de Witt; Fabio Pizzati; Katherine Elkins; Supratik Mukhopadhyay; Adel Bibi; Aaron Purewal; Botos Csaba; Fabro Steibel; Fazel Keshtkar; et al. (CoRR, 2024)

Judge a Book by its Cover: Investigating Multi-Modal LLMs for Multi-Page Handwritten Document Transcription. - Benjamin Gutteridge; Matthew Thomas Jackson; Toni Kukurin; Xiaowen Dong 001 (CoRR, 2025)

A Clean Slate for Offline Reinforcement Learning. - Matthew Thomas Jackson; Uljad Berdica; Jarek Liesen; Shimon Whiteson; Jakob Nicolaus Foerster (CoRR, 2025)

An Optimisation Framework for Unsupervised Environment Design. - Nathan Monette; Alistair Letcher; Michael Beukman; Matthew Thomas Jackson; Alexander Rutherford; Alexander David Goldie; Jakob N. Foerster (CoRR, 2025)