Matthew Thomas Jackson

According to our database, Matthew Thomas Jackson authored at least 19 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Goal-Conditioned Agents that Learn Everything All at Once.

Michael T. Matthews, Matthew Thomas Jackson, Michael Beukman, Thomas Foster, Alistair Letcher, Scott Fujimoto, Cédric Colas, Jakob N. Foerster

CoRR, May, 2026

2025

HyperVLA: Efficient Inference in Vision-Language-Action Models via Hypernetworks.

Zheng Xiong, Kang Li, Zilin Wang, Matthew Thomas Jackson, Jakob N. Foerster, Shimon Whiteson

CoRR, October, 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, May, 2025

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

CoRR, February, 2025

A Clean Slate for Offline Reinforcement Learning.

Matthew Thomas Jackson, Uljad Berdica, Jarek Liesen, Shimon Whiteson, Jakob N. Foerster

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Imagined Autocurricula.

Ahmet Hamdi Güzel, Matthew Thomas Jackson, Jarek Liesen, Tim Rocktäschel, Jakob N. Foerster, Ilija Bogunovic, Jack Parker-Holder

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

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, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan Arturo Nolazco, Lori Landay, Matthew Thomas Jackson, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster

CoRR, 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, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Thomas Jackson, Paul Röttger, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster

CoRR, 2024

Reinforcement Learning Controllers for Soft Robots Using Learned Environments.

Uljad Berdica, Matthew Thomas Jackson, Niccolò Enrico Veronese, Jakob N. Foerster, Perla Maiolino

Proceedings of the 7th IEEE International Conference on Soft Robotics, 2024

Policy-Guided Diffusion.

Matthew Thomas Jackson, Michael T. Matthews, Cong Lu, Benjamin Ellis, Shimon Whiteson, Jakob Nicolaus Foerster

RLJ, 2024

SplAgger: Split Aggregation for Meta-Reinforcement Learning.

Jacob Beck, Matthew Thomas Jackson, Risto Vuorio, Zheng Xiong, Shimon Whiteson

RLJ, 2024

Can Learned Optimization Make Reinforcement Learning Less Difficult?

Alexander David Goldie, Chris Lu, Matthew Thomas Jackson, Shimon Whiteson, Jakob N. Foerster

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 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

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 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

Proceedings of the Forty-first International Conference on Machine Learning, 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, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Thomas Jackson, Paul Röttger, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Discovering Temporally-Aware Reinforcement Learning Algorithms.

Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design.

Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob N. Foerster

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Multi-Modal Fusion by Meta-Initialization.

Matthew Thomas Jackson, Shreshth A. Malik, Michael T. Matthews, Yousuf Mohamed-Ahmed

CoRR, 2022

Hypernetworks in Meta-Reinforcement Learning.

Jacob Beck, Matthew Thomas Jackson, Risto Vuorio, Shimon Whiteson

Proceedings of the Conference on Robot Learning, 2022