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From the 1 of 11 linked papers with an AI index.

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11 papers

math.NA2026

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-…

math.NA2026

A high-order multi-scale method and its convergence analysis for temperature-dependent nonlinear thermal radiation problems of composite structures

Hao Dong, Yongfei Hu, Jiale Linghu +1

Accurate prediction of the nonlinear radiation thermal transfer in composite structures with temperature-dependent properties is significant in high-temperature applications of the…

math.NA2026

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…

math.NA2026

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…

cs.LG2026

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…

math.NA2026

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…