Matthew Thomas Jackson

According to our database1, Matthew Thomas Jackson authored at least 16 papers between 2022 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
An Optimisation Framework for Unsupervised Environment Design.
CoRR, May, 2025

A Clean Slate for Offline Reinforcement Learning.
CoRR, April, 2025

Judge a Book by its Cover: Investigating Multi-Modal LLMs for Multi-Page Handwritten Document Transcription.
CoRR, February, 2025

2024
Risks and Opportunities of Open-Source Generative AI.
CoRR, 2024

Near to Mid-term Risks and Opportunities of Open Source Generative AI.
CoRR, 2024

Reinforcement Learning Controllers for Soft Robots Using Learned Environments.
Proceedings of the 7th IEEE International Conference on Soft Robotics, 2024

Policy-Guided Diffusion.
RLJ, 2024

SplAgger: Split Aggregation for Meta-Reinforcement Learning.
RLJ, 2024

Can Learned Optimization Make Reinforcement Learning Less Difficult?
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024


Discovering Temporally-Aware Reinforcement Learning Algorithms.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design.
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.
CoRR, 2022

Hypernetworks in Meta-Reinforcement Learning.
Proceedings of the Conference on Robot Learning, 2022


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