Implicit Stochastic Gradient Descent for Training Physics-informed
Neural Networks

Implicit Stochastic Gradient Descent for Training Physics-informed Neural Networks

3 March 2023

Papers citing "Implicit Stochastic Gradient Descent for Training Physics-informed Neural Networks"

15 / 15 papers shown

Title
Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions Ameya Dilip Jagtap Yeonjong Shin Kenji Kawaguchi George Karniadakis ODL 72 134 0 20 May 2021
The Dynamics of Gradient Descent for Overparametrized Neural Networks Siddhartha Satpathi R. Srikant MLT AI4CE 38 14 0 13 May 2021
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks Sizhuang He Hanwen Wang P. Perdikaris 175 456 0 18 Dec 2020
$NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework$ NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework O. Hennigh S. Narasimhan M. A. Nabian Akshay Subramaniam Kaustubh Tangsali M. Rietmann J. Ferrandis Wonmin Byeon Z. Fang S. Choudhry PINN AI4CE 115 128 0 14 Dec 2020
When and why PINNs fail to train: A neural tangent kernel perspective Sizhuang He Xinling Yu P. Perdikaris 130 908 0 28 Jul 2020
Locally adaptive activation functions with slope recovery term for deep and physics-informed neural networks Ameya Dilip Jagtap Kenji Kawaguchi George Karniadakis ODL 61 85 0 25 Sep 2019
DeepXDE: A deep learning library for solving differential equations Lu Lu Xuhui Meng Zhiping Mao George Karniadakis PINN AI4CE 95 1,528 0 10 Jul 2019
Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks Difan Zou Yuan Cao Dongruo Zhou Quanquan Gu ODL 178 448 0 21 Nov 2018
A Convergence Theory for Deep Learning via Over-Parameterization Zeyuan Allen-Zhu Yuanzhi Li Zhao Song AI4CE ODL 242 1,462 0 09 Nov 2018
Gradient Descent Finds Global Minima of Deep Neural Networks S. Du Jason D. Lee Haochuan Li Liwei Wang Masayoshi Tomizuka ODL 192 1,135 0 09 Nov 2018
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 214 1,272 0 04 Oct 2018
On the Spectral Bias of Neural Networks Nasim Rahaman A. Baratin Devansh Arpit Felix Dräxler Min Lin Fred Hamprecht Yoshua Bengio Aaron Courville 135 1,438 0 22 Jun 2018
Stochastic Backward Euler: An Implicit Gradient Descent Algorithm for $k$ -means Clustering Penghang Yin Minh Pham Adam M. Oberman Stanley Osher FedML 60 15 0 21 Oct 2017
Towards stability and optimality in stochastic gradient descent Panos Toulis Dustin Tran E. Airoldi 67 56 0 10 May 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.8K 150,039 0 22 Dec 2014