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Sparse Deep Learning for Time Series Data: Theory and Applications

Sparse Deep Learning for Time Series Data: Theory and Applications

5 October 2023
Mingxuan Zhang
Y. Sun
Faming Liang
    AI4TS
    OOD
    BDL
ArXivPDFHTML

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

5 / 5 papers shown
Title
Sparse Deep Learning: A New Framework Immune to Local Traps and
  Miscalibration
Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration
Y. Sun
Wenjun Xiong
F. Liang
33
8
0
01 Oct 2021
Consistent Sparse Deep Learning: Theory and Computation
Consistent Sparse Deep Learning: Theory and Computation
Y. Sun
Qifan Song
F. Liang
BDL
33
28
0
25 Feb 2021
Sparsity in Deep Learning: Pruning and growth for efficient inference
  and training in neural networks
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
139
684
0
31 Jan 2021
What is the State of Neural Network Pruning?
What is the State of Neural Network Pruning?
Davis W. Blalock
Jose Javier Gonzalez Ortiz
Jonathan Frankle
John Guttag
178
1,027
0
06 Mar 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,109
0
06 Jun 2015
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