Variational operator learning: A unified paradigm marrying training neural operators and solving partial differential equations

9 April 2023

Papers citing "Variational operator learning: A unified paradigm marrying training neural operators and solving partial differential equations"

6 / 6 papers shown

Title
Structure-Preserving Operator Learning Nacime Bouziani Nicolas Boullé 25 0 0 01 Oct 2024
A Deep Conjugate Direction Method for Iteratively Solving Linear Systems Ayano Kaneda Osman Akar Jingyu Chen Victoria Kala David Hyde Joseph Teran 33 10 0 22 May 2022
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 203 2,281 0 18 Oct 2020
FEA-Net: A Physics-guided Data-driven Model for Efficient Mechanical Response Prediction Houpu Yao Yi Gao Yongming Liu AI4CE 49 66 0 31 Jan 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 226 4,453 0 23 Jan 2020
An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications E. Samaniego C. Anitescu S. Goswami Vien Minh Nguyen-Thanh Hongwei Guo Khader M. Hamdia Timon Rabczuk X. Zhuang PINN AI4CE 145 1,338 0 27 Aug 2019