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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
Causal-StoNet: Causal Inference for High-Dimensional Complex Data
Yaxin Fang, Faming Liang
With the advancement of data science, the collection of increasingly complex datasets has become commonplace. In such datasets, the data dimension can be extremely high, and the un…
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…