Sparse Deep Learning for Time Series Data: Theory and Applications

5 October 2023

Papers citing "Sparse Deep Learning for Time Series Data: Theory and Applications"

6 / 6 papers shown

Title
Magnitude Pruning of Large Pretrained Transformer Models with a Mixture Gaussian Prior Mingxuan Zhang Y. Sun F. Liang 34 0 0 01 Nov 2024
Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration Y. Sun Wenjun Xiong F. Liang 42 8 0 01 Oct 2021
Consistent Sparse Deep Learning: Theory and Computation Y. Sun Qifan Song F. Liang BDL 41 27 0 25 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 191 1,027 0 06 Mar 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015