MingSun-Tse/Awesome-Pruning-at-Initialization MingSun-Tse/Awesome-Pruning-at-Initialization

  • Stars
    star
    44
  • Rank 631,088 (Top 13 %)
  • Language
  • License
    MIT License
  • Created over 2 years ago
  • Updated over 1 year ago
Twitter logo Share LinkedIn logo Share Facebook logo Share
MingSun-Tse/Awesome-Pruning-at-Initialization
github

MingSun-Tse

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

[IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.

More Repositories

1

Efficient-Deep-Learning

Collection of recent methods on (deep) neural network compression and acceleration.
915
star
2

Collaborative-Distillation

[CVPR'20] Collaborative Distillation for Ultra-Resolution Universal Style Transfer (PyTorch)
Python
180
star
3

Regularization-Pruning

[ICLR'21] Neural Pruning via Growing Regularization (PyTorch)
Python
73
star
4

ASSL

[NeurIPS'21 Spotlight] Aligned Structured Sparsity Learning for Efficient Image Super-Resolution (PyTorch)
Python
59
star
5

Smile-Pruning

A generic code base for neural network pruning, especially for pruning at initialization.
Python
30
star
6

Good-DA-in-KD

[NeurIPS'22] What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspective
Python
29
star
7

Why-the-State-of-Pruning-so-Confusing

[Preprint] Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruning
29
star
8

smilelogging

Python logging package for easy reproducible experimenting in research
Python
25
star
9

TPP

[ICLR'23] Trainability Preserving Neural Pruning (PyTorch)
Python
23
star
10

Awesome-Efficient-ViT

Recent Advances on Efficient Vision Transformers
22
star
11

SRP

[ICLR'22] PyTorch code for our paper "Learning Efficient Image Super-Resolution Networks via Structure-Regularized Pruning"
Python
18
star
12

Caffe_IncReg

[IJCNN'19, IEEE JSTSP'19] Caffe code for our paper "Structured Pruning for Efficient ConvNets via Incremental Regularization"; [BMVC'18] "Structured Probabilistic Pruning for Convolutional Neural Network Acceleration"
Makefile
14
star
13

WritingTips

"Good scientific writing is not a matter of life and death; it is much more serious than that."
TeX
7
star
14

Efficient-NeRF

Python
7
star
15

UtilsHub

Python
3
star
16

LowlevelVision

paper collection for low-level vision
3
star
17

AdversarialAttacks

2
star