RESEARCH

Stratified Sampling Algorithms for Machine Learning Methods in Solving Two-scale Partial Differential Equations

JS-type and Z-type weights for fourth-order central-upwind weighted essentially non-oscillatory schemes

Sobolev training for operator learning

A Physics-Informed Neural Network framework for solving PDEs on point clouds via surface reconstruction

Ancient Mean Curvature Flows With Finite Total Curvature

Quantitative Pointwise Estimates of the Cooling Process for Inelastic Boltzmann Equation

Reverse engineering for programmable logic controller structure estimation via white box networks

A Neural Operator Unifying Graph Neural Networks and Point Transformers