3 papers
physics.flu-dyn2025
Addressing A Posteriori Performance Degradation in Neural Network Subgrid Stress Models
Andy Wu, Sanjiva K. Lele
Neural network subgrid stress models often have a priori performance that is far better than the a posteriori performance, leading to neural network models that look very promising…
cs.LG2025
Constant in an Ever-Changing World
Andy Wu, Chun-Cheng Lin, Yuehua Huang +1
The training process of reinforcement learning often suffers from severe oscillations, leading to instability and degraded performance. In this paper, we propose a Constant in an E…
cs.LG2025
Multi-Actor Multi-Critic Deep Deterministic Reinforcement Learning with a Novel Q-Ensemble Method
Andy Wu, Chun-Cheng Lin, Rung-Tzuo Liaw +3
Reinforcement learning has gathered much attention in recent years due to its rapid development and rich applications, especially on control systems and robotics. When tackling rea…