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Matthew Thomas Jackson
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2020 – today
- 2025
[i17]Benjamin Gutteridge, Matthew Thomas Jackson, Toni Kukurin, Xiaowen Dong:
Judge a Book by its Cover: Investigating Multi-Modal LLMs for Multi-Page Handwritten Document Transcription. CoRR abs/2502.20295 (2025)
[i16]Matthew Thomas Jackson, Uljad Berdica, Jarek Liesen, Shimon Whiteson, Jakob Nicolaus Foerster:
A Clean Slate for Offline Reinforcement Learning. CoRR abs/2504.11453 (2025)
[i15]Nathan Monette, Alistair Letcher, Michael Beukman, Matthew Thomas Jackson, Alexander Rutherford, Alexander David Goldie, Jakob N. Foerster:
An Optimisation Framework for Unsupervised Environment Design. CoRR abs/2505.20659 (2025)
[i14]Ahmet Hamdi Güzel, Matthew Thomas Jackson, Jarek Liesen, Tim Rocktäschel, Jakob Nicolaus Foerster, Ilija Bogunovic, Jack Parker-Holder:
Imagined Autocurricula. CoRR abs/2509.13341 (2025)
[i13]Zheng Xiong, Kang Li, Zilin Wang, Matthew Thomas Jackson, Jakob N. Foerster, Shimon Whiteson:
HyperVLA: Efficient Inference in Vision-Language-Action Models via Hypernetworks. CoRR abs/2510.04898 (2025)- 2024
[j2]Jacob Beck, Matthew Thomas Jackson, Risto Vuorio, Zheng Xiong, Shimon Whiteson:
SplAgger: Split Aggregation for Meta-Reinforcement Learning. RLJ 1: 450-469 (2024)
[j1]Matthew Thomas Jackson, Michael T. Matthews, Cong Lu, Benjamin Ellis, Shimon Whiteson, Jakob Nicolaus Foerster:
Policy-Guided Diffusion. RLJ 4: 1855-1872 (2024)
[c8]Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster:
Discovering Temporally-Aware Reinforcement Learning Algorithms. ICLR 2024
[c7]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:
Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI. ICML 2024
[c6]Michael T. Matthews, Michael Beukman, Benjamin Ellis, Mikayel Samvelyan, Matthew Thomas Jackson, Samuel Coward, Jakob Nicolaus Foerster:
Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning. ICML 2024
[c5]Benjamin Ellis, Matthew Thomas Jackson, Andrei Lupu, Alexander David Goldie, Mattie Fellows, Shimon Whiteson, Jakob N. Foerster:
Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps. NeurIPS 2024
[c4]Alexander David Goldie, Chris Lu, Matthew Thomas Jackson, Shimon Whiteson, Jakob N. Foerster:
Can Learned Optimization Make Reinforcement Learning Less Difficult? NeurIPS 2024
[c3]Uljad Berdica, Matthew Thomas Jackson, Niccolò Enrico Veronese, Jakob N. Foerster, Perla Maiolino:
Reinforcement Learning Controllers for Soft Robots Using Learned Environments. RoboSoft 2024: 933-939
[i12]Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert T. Lange, Shimon Whiteson, Jakob Nicolaus Foerster:
Discovering Temporally-Aware Reinforcement Learning Algorithms. CoRR abs/2402.05828 (2024)
[i11]Michael T. Matthews, Michael Beukman, Benjamin Ellis, Mikayel Samvelyan, Matthew Thomas Jackson, Samuel Coward, Jakob N. Foerster:
Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning. CoRR abs/2402.16801 (2024)
[i10]Jacob Beck, Matthew Thomas Jackson, Risto Vuorio, Zheng Xiong, Shimon Whiteson:
SplAgger: Split Aggregation for Meta-Reinforcement Learning. CoRR abs/2403.03020 (2024)
[i9]Matthew Thomas Jackson, Michael T. Matthews, Cong Lu, Benjamin Ellis, Shimon Whiteson, Jakob N. Foerster:
Policy-Guided Diffusion. CoRR abs/2404.06356 (2024)
[i8]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:
Near to Mid-term Risks and Opportunities of Open Source Generative AI. CoRR abs/2404.17047 (2024)
[i7]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:
Risks and Opportunities of Open-Source Generative AI. CoRR abs/2405.08597 (2024)
[i6]Alexander David Goldie, Chris Lu, Matthew Thomas Jackson, Shimon Whiteson, Jakob Nicolaus Foerster:
Can Learned Optimization Make Reinforcement Learning Less Difficult? CoRR abs/2407.07082 (2024)
[i5]Uljad Berdica, Matthew Thomas Jackson, Niccolò Enrico Veronese, Jakob N. Foerster, Perla Maiolino:
Reinforcement Learning Controllers for Soft Robots using Learned Environments. CoRR abs/2410.18519 (2024)
[i4]Benjamin Ellis, Matthew Thomas Jackson, Andrei Lupu, Alexander David Goldie, Mattie Fellows, Shimon Whiteson, Jakob N. Foerster:
Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps. CoRR abs/2412.17113 (2024)- 2023
[c2]Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob N. Foerster:
Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design. NeurIPS 2023
[i3]Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob Nicolaus Foerster:
Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design. CoRR abs/2310.02782 (2023)- 2022
[c1]Jacob Beck, Matthew Thomas Jackson, Risto Vuorio, Shimon Whiteson:
Hypernetworks in Meta-Reinforcement Learning. CoRL 2022: 1478-1487
[i2]Matthew Thomas Jackson, Shreshth A. Malik, Michael T. Matthews, Yousuf Mohamed-Ahmed:
Multi-Modal Fusion by Meta-Initialization. CoRR abs/2210.04843 (2022)
[i1]Jacob Beck, Matthew Thomas Jackson, Risto Vuorio, Shimon Whiteson:
Hypernetworks in Meta-Reinforcement Learning. CoRR abs/2210.11348 (2022)
Coauthor Index
aka: Jakob Nicolaus Foerster

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last updated on 2025-11-14 22:38 CET by the dblp team
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