4 papers · 1 filter
Least-Action-Guided Diffusion for Physical Extrapolation
Zhongxin Yang, Yuanwei Bin, Xiang I. A. Yang +1
Reliable extrapolation remains a central challenge for generative models in computational physics, because models trained over finite ranges of time, parameters, or geometries may…
Diffeomorphic Latent Neural Operators for Data-Efficient Learning of Solutions to Partial Differential Equations
Zan Ahmad, Shiyi Chen, Minglang Yin +4
A computed approximation of the solution operator to a system of partial differential equations (PDEs) is needed in various areas of science and engineering. Neural operators have…
Spectral Informed Neural Network: An Efficient and Low-Memory PINN
Tianchi Yu, Yiming Qi, Ivan Oseledets +1
With growing investigations into solving partial differential equations by physics-informed neural networks (PINNs), more accurate and efficient PINNs are required to meet the prac…
Early Risk Assessment Model for ICA Timing Strategy in Unstable Angina Patients Using Multi-Modal Machine Learning
Candi Zheng, Kun Liu, Yang Wang +2
Background: Invasive coronary arteriography (ICA) is recognized as the gold standard for diagnosing cardiovascular diseases, including unstable angina (UA). The challenge lies in d…