SVD Perspectives for Augmenting DeepONet Flexibility and Interpretability

27 April 2022

Papers citing "SVD Perspectives for Augmenting DeepONet Flexibility and Interpretability"

7 / 7 papers shown

Title
PeSANet: Physics-encoded Spectral Attention Network for Simulating PDE-Governed Complex Systems Han Wan Rui Zhang Qi Wang Yong Liu Hao Sun PINN 45 0 0 03 May 2025
Deciphering and integrating invariants for neural operator learning with various physical mechanisms Rui Zhang Qi Meng Zhi-Ming Ma AI4CE 30 7 0 24 Nov 2023
A Framework for Combustion Chemistry Acceleration with DeepONets Anuj Kumar T. Echekki 24 1 0 06 Apr 2023
Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation Rui Zhang Qi Meng Rongchan Zhu Yue Wang Wenlei Shi Shihua Zhang Zhi-Ming Ma Tie-Yan Liu DiffM AI4CE 51 4 0 10 Feb 2023
Lagrangian PINNs: A causality-conforming solution to failure modes of physics-informed neural networks R. Mojgani Maciej Balajewicz P. Hassanzadeh PINN 33 45 0 05 May 2022
Improved architectures and training algorithms for deep operator networks Sizhuang He Hanwen Wang P. Perdikaris AI4CE 52 105 0 04 Oct 2021
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 232 2,287 0 18 Oct 2020