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Jiachen Yang
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Year
Fake news mitigation via point process based intervention
M Farajtabar, J Yang, X Ye, H Xu, R Trivedi, E Khalil, S Li, L Song, H Zha
International Conference on Machine Learning, 1097-1106, 2017
2062017
Learning Deep Mean Field Games for Modeling Large Population Behavior
J Yang, X Ye, R Trivedi, H Xu, H Zha
International Conference on Learning Representations, 2018
101*2018
Cm3: Cooperative multi-goal multi-stage multi-agent reinforcement learning
J Yang, A Nakhaei, D Isele, K Fujimura, H Zha
International Conference on Learning Representations, 2019
982019
Deep Reinforcement Learning and Simulation as a Path Toward Precision Medicine
BK Petersen, J Yang, WS Grathwohl, C Cockrell, C Santiago, G An, ...
Journal of Computational Biology 26 (6), 597-604, 2019
87*2019
Hierarchical Cooperative Multi-Agent Reinforcement Learning with Skill Discovery
J Yang, I Borovikov, H Zha
International Conference on Autonomous Agents and Multi-Agent Systems 19 …, 2020
812020
Learning to Incentivize Other Learning Agents
J Yang, A Li, M Farajtabar, P Sunehag, E Hughes, H Zha
Advances in Neural Information Processing Systems 33, 15208--15219, 2020
622020
Integrating independent and centralized multi-agent reinforcement learning for traffic signal network optimization
Z Zhang, J Yang, H Zha
International Conference on Autonomous Agents and Multi-Agent Systems 19 …, 2020
502020
A Unified Framework for Deep Symbolic Regression
M Landajuela, CS Lee, J Yang, R Glatt, CP Santiago, I Aravena, ...
Advances in Neural Information Processing Systems 35, 33985-33998, 2022
472022
Single Episode Policy Transfer in Reinforcement Learning
J Yang, B Petersen, H Zha, D Faissol
International Conference on Learning Representations, 2019
382019
Reinforcement learning for adaptive mesh refinement
J Yang, T Dzanic, B Petersen, J Kudo, K Mittal, V Tomov, JS Camier, ...
International Conference on Artificial Intelligence and Statistics, 5997-6014, 2023
352023
Permutation Invariant Policy Optimization for Mean-Field Multi-Agent Reinforcement Learning: A Principled Approach
Y Li, L Wang, J Yang, E Wang, Z Wang, T Zhao, H Zha
arXiv preprint arXiv:2105.08268, 2021
192021
Adaptive Incentive Design with Multi-Agent Meta-Gradient Reinforcement Learning
J Yang, E Wang, R Trivedi, T Zhao, H Zha
International Conference on Autonomous Agents and Multi-Agent Systems 21 …, 2022
182022
Graphopt: Learning optimization models of graph formation
R Trivedi, J Yang, H Zha
International Conference on Machine Learning, 9603-9613, 2020
162020
Multi-Agent Reinforcement Learning for Adaptive Mesh Refinement
J Yang, K Mittal, T Dzanic, S Petrides, B Keith, B Petersen, D Faissol, ...
arXiv preprint arXiv:2211.00801, 2022
82022
Toward Multi-Fidelity Reinforcement Learning for Symbolic Optimization
FL Silva, J Yang, M Landajuela, A Goncalves, A Ladd, D Faissol, ...
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States), 2023
22023
DynAMO: Multi-agent reinforcement learning for dynamic anticipatory mesh optimization with applications to hyperbolic conservation laws
T Dzanic, K Mittal, D Kim, J Yang, S Petrides, B Keith, R Anderson
Journal of Computational Physics 506, 112924, 2024
12024
Cooperation in Multi-Agent Reinforcement Learning
J Yang
Georgia Institute of Technology, 2021
12021
Code for Value Decomposition Graph Network and environment for AMR on linear advection
J Yang, S Petrides, T Dzanic, K Mittal, R Anderson, B Keith
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States), 2023
2023
Cooperative multi-goal, multi-agent, multi-stage reinforcement learning
J Yang, AN Sarvedani, DF Isele, K Fujimura
US Patent 11,657,266, 2023
2023
Generative Design of Decision Tree Policies for Reinforcement Learning
J Pettit, CS Lee, J Yang, A Ho, BK Petersen, M Landajuela
ICML 2024 Workshop on Structured Probabilistic Inference {\&} Generative …, 0
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