Scholar
Xinliang Liu
Google Scholar ID: 9AsSTc4AAAAJ
KAUST
Numerical homogenization
Multiscale modeling
Graph neural network
AI for scientific computing
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Citations & Impact
All-time
Citations
201
H-index
7
i10-index
6
Publications
16
Co-authors
15
list available
Contact
Email
xinliang.liu@kaust.edu.sa
Publications
7 items
Optimal Neural Network Approximation via Empirical Least Squares with Deterministic Samples
2026
Cited
0
McMg: A Learned Phase-Space Multi-channel Multigrid Preconditioner for Helmholtz Equation
2026
Cited
0
Condition Numbers and Eigenvalue Spectra of Shallow Networks on Spheres
2025
Cited
0
Self-Composing Neural Operators with Depth and Accuracy Scaling via Adaptive Train-and-Unroll Approach
2025
Cited
0
OpenBreastUS: Benchmarking Neural Operators for Wave Imaging Using Breast Ultrasound Computed Tomography
2025
Cited
0
Advanced long-term earth system forecasting by learning the small-scale nature
2025
Cited
0
ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks
International Conference on Learning Representations · 2022
Cited
37
Resume (English only)
Co-authors
15 total
Co-author 1
Yu Guang Wang
Associate Professor, Shanghai Jiao Tong University, University of New South Wales
Jinchao Xu
Professor of Applied Mathematics and Computational Sciences, KAUST
Juncai He
Assistant Professor, Yau Mathematical Sciences Center, Tsinghua University
Shuhao Cao
University of Missouri–Kansas City
Shi Jin
Shanghai Jiao Tong University
Pietro Liò
Professor, University of Cambridge
Wenrui Hao
Professor of mathematics, Penn State University
