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JaxPruner: A concise library for sparsity research

JaxPruner: A concise library for sparsity research

27 April 2023
Jooyoung Lee
Wonpyo Park
Nicole Mitchell
Jonathan Pilault
J. Obando-Ceron
Han-Byul Kim
Namhoon Lee
Elias Frantar
Yun Long
Amir Yazdanbakhsh
Shivani Agrawal
Suvinay Subramanian
Xin Wang
Sheng-Chun Kao
Xingyao Zhang
Trevor Gale
Aart J. C. Bik
Woohyun Han
Milen Ferev
Zhonglin Han
Hong-Seok Kim
Yann N. Dauphin
Karolina Dziugaite
P. S. Castro
Utku Evci
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Papers citing "JaxPruner: A concise library for sparsity research"

14 / 14 papers shown
Title
Eau De QQQ-Network: Adaptive Distillation of Neural Networks in Deep Reinforcement Learning
Théo Vincent
Tim Lukas Faust
Yogesh Tripathi
Jan Peters
Carlo DÉramo
37
0
0
03 Mar 2025
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Alessandro Pierro
Steven Abreu
Jonathan Timcheck
Philipp Stratmann
Andreas Wild
S. Shrestha
65
0
0
03 Feb 2025
Navigating Extremes: Dynamic Sparsity in Large Output Spaces
Navigating Extremes: Dynamic Sparsity in Large Output Spaces
Nasib Ullah
Erik Schultheis
Mike Lasby
Yani Andrew Ioannou
Rohit Babbar
33
0
0
05 Nov 2024
Neuroplastic Expansion in Deep Reinforcement Learning
Neuroplastic Expansion in Deep Reinforcement Learning
Jiashun Liu
J. Obando-Ceron
Aaron C. Courville
L. Pan
36
3
0
10 Oct 2024
Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness
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
Maxwell's Demon at Work: Efficient Pruning by Leveraging Saturation of
  Neurons
Maxwell's Demon at Work: Efficient Pruning by Leveraging Saturation of Neurons
Simon Dufort-Labbé
P. DÓro
Evgenii Nikishin
Razvan Pascanu
Pierre-Luc Bacon
A. Baratin
32
1
0
12 Mar 2024
In value-based deep reinforcement learning, a pruned network is a good
  network
In value-based deep reinforcement learning, a pruned network is a good network
J. Obando-Ceron
Aaron C. Courville
Pablo Samuel Castro
OffRL
36
18
0
19 Feb 2024
ELSA: Partial Weight Freezing for Overhead-Free Sparse Network
  Deployment
ELSA: Partial Weight Freezing for Overhead-Free Sparse Network Deployment
Paniz Halvachi
Alexandra Peste
Dan Alistarh
Christoph H. Lampert
15
0
0
11 Dec 2023
Scaling Laws for Sparsely-Connected Foundation Models
Scaling Laws for Sparsely-Connected Foundation Models
Elias Frantar
C. Riquelme
N. Houlsby
Dan Alistarh
Utku Evci
18
35
0
15 Sep 2023
SCENIC: A JAX Library for Computer Vision Research and Beyond
SCENIC: A JAX Library for Computer Vision Research and Beyond
Mostafa Dehghani
A. Gritsenko
Anurag Arnab
Matthias Minderer
Yi Tay
43
68
0
18 Oct 2021
Accelerated Sparse Neural Training: A Provable and Efficient Method to
  Find N:M Transposable Masks
Accelerated Sparse Neural Training: A Provable and Efficient Method to Find N:M Transposable Masks
Itay Hubara
Brian Chmiel
Moshe Island
Ron Banner
S. Naor
Daniel Soudry
46
110
0
16 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
141
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
185
1,027
0
06 Mar 2020
ImageNet Large Scale Visual Recognition Challenge
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
1