Deep Neural Network Initialization with Sparsity Inducing Activations

25 February 2024

Papers citing "Deep Neural Network Initialization with Sparsity Inducing Activations"

8 / 8 papers shown

Title
The Principles of Deep Learning Theory Daniel A. Roberts Sho Yaida Boris Hanin FaML PINN GNN 37 245 0 18 Jun 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 264 703 0 31 Jan 2021
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 250 1,045 0 06 Mar 2020
Mean field theory for deep dropout networks: digging up gradient backpropagation deeply Wei Huang R. Xu Weitao Du Yutian Zeng Yunce Zhao 42 6 0 19 Dec 2019
Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs D. Gilboa B. Chang Minmin Chen Greg Yang S. Schoenholz Ed H. Chi Jeffrey Pennington 63 41 0 25 Jan 2019
SNIP: Single-shot Network Pruning based on Connection Sensitivity Namhoon Lee Thalaiyasingam Ajanthan Philip Torr VLM 217 1,190 0 04 Oct 2018
Exponential expressivity in deep neural networks through transient chaos Ben Poole Subhaneil Lahiri M. Raghu Jascha Narain Sohl-Dickstein Surya Ganguli 83 587 0 16 Jun 2016
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 264 6,628 0 08 Jun 2015