3 papers
cs.LG2025
A Tutorial on Dimensionless Learning: Geometric Interpretation and the Effect of Noise
Zhengtao Jake Gan, Xiaoyu Xie
Dimensionless learning is a data-driven framework for discovering dimensionless numbers and scaling laws from experimental measurements. This tutorial introduces the method, explai…
cs.CE2025
Convolutional Hierarchical Deep Learning Neural Networks-Tensor Decomposition (C-HiDeNN-TD): a scalable surrogate modeling approach for large-scale physical systems
Jiachen Guo, Chanwook Park, Xiaoyu Xie +3
A common trend in simulation-driven engineering applications is the ever-increasing size and complexity of the problem, where classical numerical methods typically suffer from sign…
cs.CE2025
Interpolating Neural Network-Tensor Decomposition (INN-TD): a scalable and interpretable approach for large-scale physics-based problems
Jiachen Guo, Xiaoyu Xie, Chanwook Park +5
Deep learning has been extensively employed as a powerful function approximator for modeling physics-based problems described by partial differential equations (PDEs). Despite thei…