NeuFENet: Neural Finite Element Solutions with Theoretical Bounds for
Parametric PDEs

NeuFENet: Neural Finite Element Solutions with Theoretical Bounds for Parametric PDEs

4 October 2021

Aditya Balu

A. Krishnamurthy

Baskar Ganapathysubramanian

Papers citing "NeuFENet: Neural Finite Element Solutions with Theoretical Bounds for Parametric PDEs"

8 / 8 papers shown

Title
Differentiable Neural-Integrated Meshfree Method for Forward and Inverse Modeling of Finite Strain Hyperelasticity Honghui Du Binyao Guo QiZhi He AI4CE 25 0 0 15 Jul 2024
A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains Yusuke Yamazaki Ali Harandi Mayu Muramatsu A. Viardin Markus Apel T. Brepols Stefanie Reese Shahed Rezaei AI4CE 26 12 0 21 May 2024
Learning smooth functions in high dimensions: from sparse polynomials to deep neural networks Ben Adcock Simone Brugiapaglia N. Dexter S. Moraga 25 4 0 04 Apr 2024
A Deep Learning Framework for Solving Hyperbolic Partial Differential Equations: Part I Rajat Arora PINN AI4CE 15 1 0 09 Jul 2023
CAS4DL: Christoffel Adaptive Sampling for function approximation via Deep Learning Ben Adcock Juan M. Cardenas N. Dexter 14 8 0 25 Aug 2022
SPINN: Sparse, Physics-based, and partially Interpretable Neural Networks for PDEs A. A. Ramabathiran P. Ramachandran PINN AI4CE 24 75 0 25 Feb 2021
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
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 1,333 0 27 Aug 2019