Accelerating Physics-Informed Neural Network Training with Prior Dictionaries

17 April 2020

Papers citing "Accelerating Physics-Informed Neural Network Training with Prior Dictionaries"

8 / 8 papers shown

Title
Transport-Embedded Neural Architecture: Redefining the Landscape of physics aware neural models in fluid mechanics Amirmahdi Jafari 28 0 0 05 Oct 2024
Physical Activation Functions (PAFs): An Approach for More Efficient Induction of Physics into Physics-Informed Neural Networks (PINNs) J. Abbasi Paal Ostebo Andersen PINN AI4CE 25 14 0 29 May 2022
Overview frequency principle/spectral bias in deep learning Z. Xu Yaoyu Zhang Tao Luo FaML 30 66 0 19 Jan 2022
An extended physics informed neural network for preliminary analysis of parametric optimal control problems N. Demo M. Strazzullo G. Rozza PINN 31 33 0 26 Oct 2021
Multi-Objective Loss Balancing for Physics-Informed Deep Learning Rafael Bischof M. Kraus PINN AI4CE 33 92 0 19 Oct 2021
Data vs. Physics: The Apparent Pareto Front of Physics-Informed Neural Networks Franz M. Rohrhofer S. Posch C. Gößnitzer Bernhard C. Geiger PINN 23 39 0 03 May 2021
Active Training of Physics-Informed Neural Networks to Aggregate and Interpolate Parametric Solutions to the Navier-Stokes Equations Christopher J. Arthurs A. King PINN 35 51 0 02 May 2020
$All-Optical Machine Learning Using Diffractive Deep Neural Networks$ All-Optical Machine Learning Using Diffractive Deep Neural Networks Xing Lin Y. Rivenson N. Yardimci Muhammed Veli Mona Jarrahi Aydogan Ozcan 76 1,628 0 14 Apr 2018