Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training

21 June 2023

Papers citing "Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training"

8 / 8 papers shown

Title
Sparse-to-Sparse Training of Diffusion Models Inês Cardoso Oliveira Decebal Constantin Mocanu Luis A. Leiva DiffM 86 0 0 30 Apr 2025
Navigating Extremes: Dynamic Sparsity in Large Output Spaces Nasib Ullah Erik Schultheis Mike Lasby Yani Andrew Ioannou Rohit Babbar 35 0 0 05 Nov 2024
RelChaNet: Neural Network Feature Selection using Relative Change Scores Felix Zimmer 24 0 0 03 Oct 2024
Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness Boqian Wu Q. Xiao Shunxin Wang N. Strisciuglio Mykola Pechenizkiy M. V. Keulen D. Mocanu Elena Mocanu OOD 3DH 52 0 0 03 Oct 2024
Truly Sparse Neural Networks at Scale Selima Curci D. Mocanu Mykola Pechenizkiy 28 19 0 02 Feb 2021
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 188 1,027 0 06 Mar 2020
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 296 39,194 0 01 Sep 2014