47 citations · 57 across the 9 of their papers we have counts for
5 papers · 1 filter
Deep reinforcement learning for process design: Review and perspective
Qinghe Gao, Artur M. Schweidtmann
The transformation towards renewable energy and feedstock supply in the chemical industry requires new conceptual process design approaches. Recently, breakthroughs in artificial i…
Robust Reinforcement Learning through Efficient Adversarial Herding
Juncheng Dong, Hao-Lun Hsu, Qitong Gao +2
Although reinforcement learning (RL) is considered the gold standard for policy design, it may not always provide a robust solution in various scenarios. This can result in severe…
Offline Learning of Closed-Loop Deep Brain Stimulation Controllers for Parkinson Disease Treatment
Qitong Gao, Stephen L. Schimdt, Afsana Chowdhury +6
Deep brain stimulation (DBS) has shown great promise toward treating motor symptoms caused by Parkinson's disease (PD), by delivering electrical pulses to the Basal Ganglia (BG) re…
Transfer learning for process design with reinforcement learning
Qinghe Gao, Haoyu Yang, Shachi M. Shanbhag +1
Process design is a creative task that is currently performed manually by engineers. Artificial intelligence provides new potential to facilitate process design. Specifically, rein…
Variational Latent Branching Model for Off-Policy Evaluation
Qitong Gao, Ge Gao, Min Chi +1
Model-based methods have recently shown great potential for off-policy evaluation (OPE); offline trajectories induced by behavioral policies are fitted to transitions of Markov dec…