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cs.LG2025
Variational Geometry-aware Neural Network based Method for Solving High-dimensional Diffeomorphic Mapping Problems
Zhiwen Li, Cheuk Hin Ho, Lok Ming Lui
Traditional methods for high-dimensional diffeomorphic mapping often struggle with the curse of dimensionality. We propose a mesh-free learning framework designed for -dimension…
cs.LG2025
A Conformal Prediction Framework for Uncertainty Quantification in Physics-Informed Neural Networks
Yifan Yu, Cheuk Hin Ho, Yangshuai Wang
Physics-Informed Neural Networks (PINNs) have emerged as a powerful framework for solving PDEs, yet existing uncertainty quantification (UQ) approaches for PINNs generally lack rig…