Extreme sparsification of physics-augmented neural networks for interpretable model discovery in mechanics

5 October 2023

Papers citing "Extreme sparsification of physics-augmented neural networks for interpretable model discovery in mechanics"

4 / 4 papers shown

Title
Input convex neural networks: universal approximation theorem and implementation for isotropic polyconvex hyperelastic energies Gian-Luca Geuken P. Kurzeja David Wiedemann J. Mosler 57 1 0 12 Feb 2025
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 141 684 0 31 Jan 2021
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 191 1,027 0 06 Mar 2020
Input Convex Neural Networks Brandon Amos Lei Xu J. Zico Kolter 187 599 0 22 Sep 2016