Minqi Jiang

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 51

Top Topics

Weakly Supervised

Reinforcement Learning

Top Venues

Publications

Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Akbir Khan, Christian Schröder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert T. Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob N. Foerster
JaxMARL: Multi-Agent RL Environments and Algorithms in JAX. AAMAS (2024)
Mikayel Samvelyan, Davide Paglieri, Minqi Jiang, Jack Parker-Holder, Tim Rocktäschel
Multi-Agent Diagnostics for Robustness via Illuminated Diversity. AAMAS (2024)
Mikayel Samvelyan, Davide Paglieri, Minqi Jiang, Jack Parker-Holder, Tim Rocktäschel
Multi-Agent Diagnostics for Robustness via Illuminated Diversity. CoRR (2024)
Ishita Mediratta, Qingfei You, Minqi Jiang, Roberta Raileanu
The Generalization Gap in Offline Reinforcement Learning. ICLR (2024)
Mikayel Samvelyan, Sharath Chandra Raparthy, Andrei Lupu, Eric Hambro, Aram H. Markosyan, Manish Bhatt, Yuning Mao, Minqi Jiang, Jack Parker-Holder, Jakob N. Foerster, Tim Rocktäschel, Roberta Raileanu
Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts. CoRR (2024)
Dominik Schmidt, Minqi Jiang
Learning to Act without Actions. ICLR (2024)
Marc Rigter, Minqi Jiang, Ingmar Posner
Reward-Free Curricula for Training Robust World Models. ICLR (2024)
Michael Beukman, Samuel Coward, Michael Matthews, Mattie Fellows, Minqi Jiang, Michael Dennis, Jakob N. Foerster
Refining Minimax Regret for Unsupervised Environment Design. CoRR (2024)
Minqi Jiang, Songqiao Han, Hailiang Huang
Anomaly Detection with Score Distribution Discrimination. CoRR (2023)
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)
Minqi Jiang, Chaochuan Hou, Ao Zheng, Songqiao Han, Hailiang Huang, Qingsong Wen, Xiyang Hu, Yue Zhao
ADGym: Design Choices for Deep Anomaly Detection. NeurIPS (2023)
Mikayel Samvelyan, Akbir Khan, Michael Dennis, Minqi Jiang, Jack Parker-Holder, Jakob N. Foerster, Roberta Raileanu, Tim Rocktäschel
MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning. CoRR (2023)
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 (2023)
Mikayel Samvelyan, Akbir Khan, Michael Dennis, Minqi Jiang, Jack Parker-Holder, Jakob Nicolaus Foerster, Roberta Raileanu, Tim Rocktäschel
MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning. ICLR (2023)
Minqi Jiang, Songqiao Han, Hailiang Huang
Anomaly Detection with Score Distribution Discrimination. KDD (2023)
Minqi Jiang, Michael Dennis, Edward Grefenstette, Tim Rocktäschel
minimax: Efficient Baselines for Autocurricula in JAX. CoRR (2023)
Mikael Henaff, Minqi Jiang, Roberta Raileanu
A Study of Global and Episodic Bonuses for Exploration in Contextual MDPs. CoRR (2023)
Ishita Mediratta, Qingfei You, Minqi Jiang, Roberta Raileanu
The Generalization Gap in Offline Reinforcement Learning. CoRR (2023)
Minqi Jiang
Learning Curricula in Open-Ended Worlds. CoRR (2023)
Biyang Guo, Xin Zhang, Ziyuan Wang, Minqi Jiang, Jinran Nie, Yuxuan Ding, Jianwei Yue, Yupeng Wu
How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection. CoRR (2023)
Minqi Jiang, Chaochuan Hou, Ao Zheng, Xiyang Hu, Songqiao Han, Hailiang Huang, Xiangnan He, Philip S. Yu, Yue Zhao
Weakly Supervised Anomaly Detection: A Survey. CoRR (2023)
Mikael Henaff, Minqi Jiang, Roberta Raileanu
A Study of Global and Episodic Bonuses for Exploration in Contextual MDPs. ICML (2023)
Ishita Mediratta, Minqi Jiang, Jack Parker-Holder, Michael Dennis, Eugene Vinitsky, Tim Rocktäschel
Stabilizing Unsupervised Environment Design with a Learned Adversary. CoLLAs (2023)
Dominik Schmidt, Minqi Jiang
Learning to Act without Actions. CoRR (2023)
Ishita Mediratta, Minqi Jiang, Jack Parker-Holder, Michael Dennis, Eugene Vinitsky, Tim Rocktäschel
Stabilizing Unsupervised Environment Design with a Learned Adversary. CoRR (2023)
Marc Rigter, Minqi Jiang, Ingmar Posner
Reward-Free Curricula for Training Robust World Models. CoRR (2023)
Minqi Jiang, Chaochuan Hou, Ao Zheng, Songqiao Han, Hailiang Huang, Qingsong Wen, Xiyang Hu, Yue Zhao
ADGym: Design Choices for Deep Anomaly Detection. CoRR (2023)
Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Akbir Khan, Christian Schröder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert Tjarko Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob Nicolaus Foerster
JaxMARL: Multi-Agent RL Environments in JAX. CoRR (2023)
Mikael Henaff, Roberta Raileanu, Minqi Jiang, Tim Rocktäschel
Exploration via Elliptical Episodic Bonuses. NeurIPS (2022)
Minqi Jiang, Tim Rocktäschel, Edward Grefenstette
General Intelligence Requires Rethinking Exploration. CoRR (2022)
Jack Parker-Holder, Minqi Jiang, Michael Dennis, Mikayel Samvelyan, Jakob N. Foerster, Edward Grefenstette, Tim Rocktäschel
Evolving Curricula with Regret-Based Environment Design. ICML (2022)
Songqiao Han, Xiyang Hu, Hailiang Huang, Minqi Jiang, Yue Zhao
ADBench: Anomaly Detection Benchmark. NeurIPS (2022)
Christopher Bamford, Minqi Jiang, Mikayel Samvelyan, Tim Rocktäschel
GriddlyJS: A Web IDE for Reinforcement Learning. CoRR (2022)
Minqi Jiang, Michael Dennis, Jack Parker-Holder, Andrei Lupu, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel, Jakob N. Foerster
Grounding Aleatoric Uncertainty for Unsupervised Environment Design. NeurIPS (2022)
Eric Hambro, Sharada P. Mohanty, Dmitrii Babaev, Minwoo Byeon, Dipam Chakraborty, Edward Grefenstette, Minqi Jiang, DaeJin Jo, Anssi Kanervisto, Jongmin Kim, Sungwoong Kim, Robert Kirk, Vitaly Kurin, Heinrich Küttler, Taehwon Kwon, Donghoon Lee, Vegard Mella, Nantas Nardelli, Ivan Nazarov, Nikita Ovsov, Jack Parker-Holder, Roberta Raileanu, Karolis Ramanauskas, Tim Rocktäschel, Danielle Rothermel, Mikayel Samvelyan, Dmitry Sorokin, Maciej Sypetkowski, Michal Sypetkowski
Insights From the NeurIPS 2021 NetHack Challenge. CoRR (2022)
Jesse Mu, Victor Zhong, Roberta Raileanu, Minqi Jiang, Noah D. Goodman, Tim Rocktäschel, Edward Grefenstette
Improving Intrinsic Exploration with Language Abstractions. NeurIPS (2022)
Jack Parker-Holder, Minqi Jiang, Michael Dennis, Mikayel Samvelyan, Jakob Foerster, Edward Grefenstette, Tim Rocktäschel
Evolving Curricula with Regret-Based Environment Design. CoRR (2022)
Christopher Bamford, Minqi Jiang, Mikayel Samvelyan, Tim Rocktäschel
GriddlyJS: A Web IDE for Reinforcement Learning. NeurIPS (2022)
Jesse Mu, Victor Zhong, Roberta Raileanu, Minqi Jiang, Noah D. Goodman, Tim Rocktäschel, Edward Grefenstette
Improving Intrinsic Exploration with Language Abstractions. CoRR (2022)
Minqi Jiang, Michael Dennis, Jack Parker-Holder, Andrei Lupu, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel, Jakob N. Foerster
Grounding Aleatoric Uncertainty in Unsupervised Environment Design. CoRR (2022)
Mikael Henaff, Roberta Raileanu, Minqi Jiang, Tim Rocktäschel
Exploration via Elliptical Episodic Bonuses. CoRR (2022)
Minqi Jiang, Michael Dennis, Jack Parker-Holder, Jakob Foerster, Edward Grefenstette, Tim Rocktäschel
Replay-Guided Adversarial Environment Design. CoRR (2021)
Eric Hambro, Sharada P. Mohanty, Dmitrii Babaev, Minwoo Byeon, Dipam Chakraborty, Edward Grefenstette, Minqi Jiang, DaeJin Jo, Anssi Kanervisto, Jongmin Kim, Sungwoong Kim, Robert Kirk, Vitaly Kurin, Heinrich Küttler, Taehwon Kwon, Donghoon Lee, Vegard Mella, Nantas Nardelli, Ivan Nazarov, Nikita Ovsov, Jack Holder, Roberta Raileanu, Karolis Ramanauskas, Tim Rocktäschel, Danielle Rothermel, Mikayel Samvelyan, Dmitry Sorokin, Maciej Sypetkowski, Michal Sypetkowski
Insights From the NeurIPS 2021 NetHack Challenge. NeurIPS (Competition and Demos) (2021)
Mikayel Samvelyan, Robert Kirk, Vitaly Kurin, Jack Parker-Holder, Minqi Jiang, Eric Hambro, Fabio Petroni, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel
MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research. NeurIPS Datasets and Benchmarks (2021)
Minqi Jiang, Edward Grefenstette, Tim Rocktäschel
Prioritized Level Replay. ICML (2021)
Zhengyao Jiang, Pasquale Minervini, Minqi Jiang, Tim Rocktäschel
Grid-to-Graph: Flexible Spatial Relational Inductive Biases for Reinforcement Learning. AAMAS (2021)
Zhengyao Jiang, Pasquale Minervini, Minqi Jiang, Tim Rocktäschel
Grid-to-Graph: Flexible Spatial Relational Inductive Biases for Reinforcement Learning. CoRR (2021)
Mikayel Samvelyan, Robert Kirk, Vitaly Kurin, Jack Parker-Holder, Minqi Jiang, Eric Hambro, Fabio Petroni, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel
MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research. CoRR (2021)
Minqi Jiang, Michael Dennis, Jack Parker-Holder, Jakob N. Foerster, Edward Grefenstette, Tim Rocktäschel
Replay-Guided Adversarial Environment Design. NeurIPS (2021)
Minqi Jiang, Edward Grefenstette, Tim Rocktäschel
Prioritized Level Replay. CoRR (2020)
Minqi Jiang, Jelena Luketina, Nantas Nardelli, Pasquale Minervini, Philip H. S. Torr, Shimon Whiteson, Tim Rocktäschel
WordCraft: An Environment for Benchmarking Commonsense Agents. CoRR (2020)