Matthew Thomas Jackson

According to our database, Matthew Thomas Jackson authored at least 12 papers between 2022 and 2024.

Collaborative distances:

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

2024

Can Learned Optimization Make Reinforcement Learning Less Difficult?

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

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, 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

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