From the 1 of 17 linked papers with an AI index.
17 papers
Efficient higher-order multi-scale method and its convergence estimate for dynamic nonlinear hygro-thermo-mechanical coupling problems of heterogeneous structures
Yifei Ding, Hao Dong, Jiale Linghu +1
This paper presents a novel higher-order multi-scale (HOMS) computational framework for efficient, high-accuracy, and low-cost simulation of nonlinear hygro-thermo-mechanical (H-T-…
A Structure-Adaptive Random Feature Method for High-Dimensional Elliptic PDEs
Jiale Linghu, Hao Dong, Yangshuai Wang
Random-feature methods reduce high-dimensional elliptic PDE collocation to linear coefficient problems, but full-dimensional trial spaces overlook lower-dimensional structure. We i…
Residual-Christoffel Sampling for Random Feature Collocation of Linear PDEs
Jiale Linghu, Yangshuai Wang
The paper proposes a new operator‑aware random feature collocation method for linear PDEs that uses residual‑Christoffel sampling and coefficient whitening to improve stability and…
Trainable Photonic Measurement for Physics-Informed PDE Learning
Jiale Linghu, Hao Dong, Yangshuai Wang
Photonic quantum machine learning offers a route to trainable physical representations built from phase, interference and measurement. However, its role in scientific machine learn…
Random-Feature Kalman Filtering for Linear PDE Data Assimilation
Xi'an Li, Jiale Linghu, Yangshuai Wang
Data assimilation for time-dependent partial differential equations (PDEs) requires Bayesian updates of an evolving field from streaming, sparse, and noisy observations, while keep…
Liquid Random Feature Methods for Time-Dependent Partial Differential Equations
Jiale Linghu, Yangshuai Wang
A central challenge in mesh-free space--time approximation for time-dependent partial differential equations is to represent evolving temporal scales while keeping residual minimiz…