1 citations · 1 across the 1 of their papers we have counts for
2 papers
stat.ML2025
Uncertainty Quantification for Physics-Informed Neural Networks with Extended Fiducial Inference
Frank Shih, Zhenghao Jiang, Faming Liang
Uncertainty quantification (UQ) in scientific machine learning is increasingly critical as neural networks are widely adopted to tackle complex problems across diverse scientific d…
stat.ML2024★ 1 cited
Fast Value Tracking for Deep Reinforcement Learning
Frank Shih, Faming Liang
Reinforcement learning (RL) tackles sequential decision-making problems by creating agents that interacts with their environment. However, existing algorithms often view these prob…