Jiachen Yang
Cited by
Cited by
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
Learning Deep Mean Field Games for Modeling Large Population Behavior
J Yang, X Ye, R Trivedi, H Xu, H Zha
arXiv preprint arXiv:1711.03156, 2017
CM3: Cooperative multi-goal multi-stage multi-agent reinforcement learning
J Yang, A Nakhaei, D Isele, K Fujimura, H Zha
arXiv preprint arXiv:1809.05188, 2018
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
Precision medicine as a control problem: Using simulation and deep reinforcement learning to discover adaptive, personalized multi-cytokine therapy for sepsis
BK Petersen, J Yang, WS Grathwohl, C Cockrell, C Santiago, G An, ...
arXiv preprint arXiv:1802.10440, 2018
Single Episode Policy Transfer in Reinforcement Learning
J Yang, B Petersen, H Zha, D Faissol
arXiv preprint arXiv:1910.07719, 2019
Integrating independent and centralized multi-agent reinforcement learning for traffic signal network optimization
Z Zhang, J Yang, H Zha
arXiv preprint arXiv:1909.10651, 2019
Graphopt: Learning optimization models of graph formation
R Trivedi, J Yang, H Zha
International Conference on Machine Learning, 9603-9613, 2020
Hierarchical Cooperative Multi-Agent Reinforcement Learning with Skill Discovery
J Yang, I Borovikov, H Zha
arXiv preprint arXiv:1912.03558, 2019
Learning to Incentivize Other Learning Agents
J Yang, A Li, M Farajtabar, P Sunehag, E Hughes, H Zha
arXiv preprint arXiv:2006.06051, 2020
Reinforcement Learning for Adaptive Mesh Refinement
J Yang, T Dzanic, B Petersen, J Kudo, K Mittal, V Tomov, JS Camier, ...
arXiv preprint arXiv:2103.01342, 2021
Single Episode Policy Transfer
BK Petersen, DM Faissol, J Yang
Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2019
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