6 citations · 14 across the 6 of their papers we have counts for
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cs.LG2024★ 2 cited
Scalable Normalizing Flows Enable Boltzmann Generators for Macromolecules
Joseph C. Kim, David Bloore, Karan Kapoor +3
The Boltzmann distribution of a protein provides a roadmap to all of its functional states. Normalizing flows are a promising tool for modeling this distribution, but current metho…
cs.LG2019
Voting-Based Multi-Agent Reinforcement Learning for Intelligent IoT
Yue Xu, Zengde Deng, Mengdi Wang +3
The recent success of single-agent reinforcement learning (RL) in Internet of things (IoT) systems motivates the study of multi-agent reinforcement learning (MARL), which is more c…
cs.LG2019★ 6 cited
RL4health: Crowdsourcing Reinforcement Learning for Knee Replacement Pathway Optimization
Hao Lu, Mengdi Wang
Joint replacement is the most common inpatient surgical treatment in the US. We investigate the clinical pathway optimization for knee replacement, which is a sequential decision p…