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Variational Dropout Sparsifies Deep Neural Networks

Variational Dropout Sparsifies Deep Neural Networks

19 January 2017
Dmitry Molchanov
Arsenii Ashukha
Dmitry Vetrov
    BDL
ArXivPDFHTML

Papers citing "Variational Dropout Sparsifies Deep Neural Networks"

50 / 122 papers shown
Title
Task-Oriented Communications for Visual Navigation with Edge-Aerial Collaboration in Low Altitude Economy
Task-Oriented Communications for Visual Navigation with Edge-Aerial Collaboration in Low Altitude Economy
Zhengru Fang
Zhenghao Liu
Jingjing Wang
Senkang Hu
Yu Guo
Yiqin Deng
Yuguang Fang
25
1
0
25 Apr 2025
Regularization can make diffusion models more efficient
Regularization can make diffusion models more efficient
Mahsa Taheri
Johannes Lederer
98
0
0
13 Feb 2025
Advancing Weight and Channel Sparsification with Enhanced Saliency
Advancing Weight and Channel Sparsification with Enhanced Saliency
Xinglong Sun
Maying Shen
Hongxu Yin
Lei Mao
Pavlo Molchanov
Jose M. Alvarez
46
1
0
05 Feb 2025
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks
Kaizheng Wang
Keivan K1 Shariatmadar
Shireen Kudukkil Manchingal
Fabio Cuzzolin
David Moens
Hans Hallez
UQCV
BDL
87
12
0
28 Jan 2025
AdapMTL: Adaptive Pruning Framework for Multitask Learning Model
AdapMTL: Adaptive Pruning Framework for Multitask Learning Model
Mingcan Xiang
Steven Jiaxun Tang
Qizheng Yang
Hui Guan
Tongping Liu
VLM
34
0
0
07 Aug 2024
The Impact of Quantization and Pruning on Deep Reinforcement Learning
  Models
The Impact of Quantization and Pruning on Deep Reinforcement Learning Models
Heng Lu
Mehdi Alemi
Reza Rawassizadeh
34
1
0
05 Jul 2024
Geometric sparsification in recurrent neural networks
Geometric sparsification in recurrent neural networks
Wyatt Mackey
Ioannis Schizas
Jared Deighton
David L. Boothe, Jr.
Vasileios Maroulas
28
0
0
10 Jun 2024
Towards Understanding Task-agnostic Debiasing Through the Lenses of
  Intrinsic Bias and Forgetfulness
Towards Understanding Task-agnostic Debiasing Through the Lenses of Intrinsic Bias and Forgetfulness
Guangliang Liu
Milad Afshari
Xitong Zhang
Zhiyu Xue
Avrajit Ghosh
Bidhan Bashyal
Rongrong Wang
K. Johnson
27
0
0
06 Jun 2024
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification
Kaizheng Wang
Fabio Cuzzolin
Keivan K1 Shariatmadar
David Moens
Hans Hallez
UQCV
BDL
70
6
0
23 May 2024
Neural Network Compression for Reinforcement Learning Tasks
Neural Network Compression for Reinforcement Learning Tasks
Dmitry A. Ivanov
D. Larionov
Oleg V. Maslennikov
V. Voevodin
OffRL
AI4CE
41
0
0
13 May 2024
Fast and Controllable Post-training Sparsity: Learning Optimal Sparsity
  Allocation with Global Constraint in Minutes
Fast and Controllable Post-training Sparsity: Learning Optimal Sparsity Allocation with Global Constraint in Minutes
Ruihao Gong
Yang Yong
Zining Wang
Jinyang Guo
Xiuying Wei
Yuqing Ma
Xianglong Liu
31
5
0
09 May 2024
Stochastic Subnetwork Annealing: A Regularization Technique for Fine
  Tuning Pruned Subnetworks
Stochastic Subnetwork Annealing: A Regularization Technique for Fine Tuning Pruned Subnetworks
Tim Whitaker
Darrell Whitley
25
0
0
16 Jan 2024
Always-Sparse Training by Growing Connections with Guided Stochastic Exploration
Always-Sparse Training by Growing Connections with Guided Stochastic Exploration
Mike Heddes
Narayan Srinivasa
T. Givargis
Alexandru Nicolau
91
0
0
12 Jan 2024
Sparsified Model Zoo Twins: Investigating Populations of Sparsified
  Neural Network Models
Sparsified Model Zoo Twins: Investigating Populations of Sparsified Neural Network Models
D. Honegger
Konstantin Schurholt
Damian Borth
20
4
0
26 Apr 2023
Learning Sparsity of Representations with Discrete Latent Variables
Learning Sparsity of Representations with Discrete Latent Variables
Zhao Xu
Daniel Oñoro-Rubio
G. Serra
Mathias Niepert
13
0
0
03 Apr 2023
Automatic Attention Pruning: Improving and Automating Model Pruning
  using Attentions
Automatic Attention Pruning: Improving and Automating Model Pruning using Attentions
Kaiqi Zhao
Animesh Jain
Ming Zhao
19
9
0
14 Mar 2023
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!
Shiwei Liu
Tianlong Chen
Zhenyu (Allen) Zhang
Xuxi Chen
Tianjin Huang
Ajay Jaiswal
Zhangyang Wang
24
29
0
03 Mar 2023
Fast as CHITA: Neural Network Pruning with Combinatorial Optimization
Fast as CHITA: Neural Network Pruning with Combinatorial Optimization
Riade Benbaki
Wenyu Chen
X. Meng
Hussein Hazimeh
Natalia Ponomareva
Zhe Zhao
Rahul Mazumder
13
26
0
28 Feb 2023
Considering Layerwise Importance in the Lottery Ticket Hypothesis
Considering Layerwise Importance in the Lottery Ticket Hypothesis
Benjamin Vandersmissen
José Oramas
15
1
0
22 Feb 2023
Differentiable Rendering with Reparameterized Volume Sampling
Differentiable Rendering with Reparameterized Volume Sampling
Nikita Morozov
D. Rakitin
Oleg Desheulin
Dmitry Vetrov
Kirill Struminsky
14
4
0
21 Feb 2023
Masked Vector Quantization
David D. Nguyen
David Leibowitz
Surya Nepal
S. Kanhere
MQ
11
0
0
16 Jan 2023
COLT: Cyclic Overlapping Lottery Tickets for Faster Pruning of Convolutional Neural Networks
COLT: Cyclic Overlapping Lottery Tickets for Faster Pruning of Convolutional Neural Networks
Md. Ismail Hossain
Mohammed Rakib
M. M. L. Elahi
Nabeel Mohammed
Shafin Rahman
21
1
0
24 Dec 2022
Hyperspherical Quantization: Toward Smaller and More Accurate Models
Hyperspherical Quantization: Toward Smaller and More Accurate Models
Dan Liu
X. Chen
Chen-li Ma
Xue Liu
MQ
22
3
0
24 Dec 2022
Pruning On-the-Fly: A Recoverable Pruning Method without Fine-tuning
Pruning On-the-Fly: A Recoverable Pruning Method without Fine-tuning
Danyang Liu
Xue Liu
12
0
0
24 Dec 2022
MP-GELU Bayesian Neural Networks: Moment Propagation by GELU
  Nonlinearity
MP-GELU Bayesian Neural Networks: Moment Propagation by GELU Nonlinearity
Yuki Hirayama
Sinya Takamaeda-Yamazaki
BDL
17
0
0
24 Nov 2022
Reverse Survival Model (RSM): A Pipeline for Explaining Predictions of
  Deep Survival Models
Reverse Survival Model (RSM): A Pipeline for Explaining Predictions of Deep Survival Models
Mohammadreza Rezaei
Reza Saadati Fard
Ebrahim Pourjafari
Navid Ziaei
Amir Sameizadeh
M. Shafiee
M. Alavinia
M. Abolghasemian
Nick Sajadi
17
1
0
27 Oct 2022
Fast and Low-Memory Deep Neural Networks Using Binary Matrix
  Factorization
Fast and Low-Memory Deep Neural Networks Using Binary Matrix Factorization
Alireza Bordbar
M. Kahaei
MQ
20
0
0
24 Oct 2022
Packed-Ensembles for Efficient Uncertainty Estimation
Packed-Ensembles for Efficient Uncertainty Estimation
Olivier Laurent
Adrien Lafage
Enzo Tartaglione
Geoffrey Daniel
Jean-Marc Martinez
Andrei Bursuc
Gianni Franchi
OODD
38
32
0
17 Oct 2022
Designing and Training of Lightweight Neural Networks on Edge Devices
  using Early Halting in Knowledge Distillation
Designing and Training of Lightweight Neural Networks on Edge Devices using Early Halting in Knowledge Distillation
Rahul Mishra
Hari Prabhat Gupta
27
8
0
30 Sep 2022
Batch Normalization Explained
Batch Normalization Explained
Randall Balestriero
Richard G. Baraniuk
AAML
28
16
0
29 Sep 2022
Compressed Gastric Image Generation Based on Soft-Label Dataset
  Distillation for Medical Data Sharing
Compressed Gastric Image Generation Based on Soft-Label Dataset Distillation for Medical Data Sharing
Guang Li
Ren Togo
Takahiro Ogawa
Miki Haseyama
DD
22
40
0
29 Sep 2022
Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs
Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs
Ðorðe Miladinovic
Kumar Shridhar
Kushal Kumar Jain
Max B. Paulus
J. M. Buhmann
Mrinmaya Sachan
Carl Allen
DRL
21
5
0
26 Sep 2022
SBPF: Sensitiveness Based Pruning Framework For Convolutional Neural
  Network On Image Classification
SBPF: Sensitiveness Based Pruning Framework For Convolutional Neural Network On Image Classification
Yihe Lu
Maoguo Gong
Wei Zhao
Kaiyuan Feng
Hao Li
VLM
29
0
0
09 Aug 2022
Minimum Description Length Control
Minimum Description Length Control
Theodore H. Moskovitz
Ta-Chu Kao
M. Sahani
M. Botvinick
18
1
0
17 Jul 2022
Collaborative Quantization Embeddings for Intra-Subject Prostate MR
  Image Registration
Collaborative Quantization Embeddings for Intra-Subject Prostate MR Image Registration
Ziyi Shen
Qianye Yang
Yuming Shen
F. Giganti
V. Stavrinides
...
M. Rusu
G. Sonn
Philip H. S. Torr
D. Barratt
Yipeng Hu
22
2
0
13 Jul 2022
Sparse Double Descent: Where Network Pruning Aggravates Overfitting
Sparse Double Descent: Where Network Pruning Aggravates Overfitting
Zhengqi He
Zeke Xie
Quanzhi Zhu
Zengchang Qin
67
27
0
17 Jun 2022
Density Regression and Uncertainty Quantification with Bayesian Deep
  Noise Neural Networks
Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks
Daiwei Zhang
Tianci Liu
Jian Kang
BDL
UQCV
24
2
0
12 Jun 2022
Statistical Guarantees for Approximate Stationary Points of Simple
  Neural Networks
Statistical Guarantees for Approximate Stationary Points of Simple Neural Networks
Mahsa Taheri
Fang Xie
Johannes Lederer
21
0
0
09 May 2022
A Survey on Dropout Methods and Experimental Verification in
  Recommendation
A Survey on Dropout Methods and Experimental Verification in Recommendation
Y. Li
Weizhi Ma
C. L. Philip Chen
M. Zhang
Yiqun Liu
Shaoping Ma
Yue Yang
27
9
0
05 Apr 2022
Improve Convolutional Neural Network Pruning by Maximizing Filter
  Variety
Improve Convolutional Neural Network Pruning by Maximizing Filter Variety
Nathan Hubens
M. Mancas
B. Gosselin
Marius Preda
T. Zaharia
11
2
0
11 Mar 2022
MaxDropoutV2: An Improved Method to Drop out Neurons in Convolutional
  Neural Networks
MaxDropoutV2: An Improved Method to Drop out Neurons in Convolutional Neural Networks
C. F. G. Santos
Mateus Roder
L. A. Passos
João Paulo Papa
19
1
0
05 Mar 2022
The rise of the lottery heroes: why zero-shot pruning is hard
The rise of the lottery heroes: why zero-shot pruning is hard
Enzo Tartaglione
21
6
0
24 Feb 2022
Bayesian Model Selection, the Marginal Likelihood, and Generalization
Bayesian Model Selection, the Marginal Likelihood, and Generalization
Sanae Lotfi
Pavel Izmailov
Gregory W. Benton
Micah Goldblum
A. Wilson
UQCV
BDL
52
56
0
23 Feb 2022
Sparsity Winning Twice: Better Robust Generalization from More Efficient
  Training
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training
Tianlong Chen
Zhenyu (Allen) Zhang
Pengju Wang
Santosh Balachandra
Haoyu Ma
Zehao Wang
Zhangyang Wang
OOD
AAML
77
46
0
20 Feb 2022
Recursive Least Squares for Training and Pruning Convolutional Neural
  Networks
Recursive Least Squares for Training and Pruning Convolutional Neural Networks
Tianzong Yu
Chunyuan Zhang
Yuan Wang
Meng-tao Ma
Qingwei Song
22
1
0
13 Jan 2022
Probabilistic Approach for Road-Users Detection
Probabilistic Approach for Road-Users Detection
Gledson Melotti
Weihao Lu
Pedro Conde
Dezong Zhao
A. Asvadi
Nuno Gonçalves
C. Premebida
19
2
0
02 Dec 2021
How Well Do Sparse Imagenet Models Transfer?
How Well Do Sparse Imagenet Models Transfer?
Eugenia Iofinova
Alexandra Peste
Mark Kurtz
Dan Alistarh
19
38
0
26 Nov 2021
Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma
  Distributions
Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions
Huan Ma
Zongbo Han
Changqing Zhang
H. Fu
Joey Tianyi Zhou
Q. Hu
EDL
UQCV
66
42
0
11 Nov 2021
MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the
  Edge
MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge
Geng Yuan
Xiaolong Ma
Wei Niu
Zhengang Li
Zhenglun Kong
...
Minghai Qin
Bin Ren
Yanzhi Wang
Sijia Liu
Xue Lin
15
89
0
26 Oct 2021
Probabilistic fine-tuning of pruning masks and PAC-Bayes self-bounded
  learning
Probabilistic fine-tuning of pruning masks and PAC-Bayes self-bounded learning
Soufiane Hayou
Bo He
Gintare Karolina Dziugaite
11
2
0
22 Oct 2021
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