A curated list of neural network pruning resources.

Overview

Awesome Pruning Awesome

A curated list of neural network pruning and related resources. Inspired by awesome-deep-vision, awesome-adversarial-machine-learning, awesome-deep-learning-papers and Awesome-NAS.

Please feel free to pull requests or open an issue to add papers.

Table of Contents

Type of Pruning

Type F W Other
Explanation Filter pruning Weight pruning other types

2020

Title Venue Type Code
HYDRA: Pruning Adversarially Robust Neural Networks NeurIPS W PyTorch(Author)
Logarithmic Pruning is All You Need NeurIPS W -
Directional Pruning of Deep Neural Networks NeurIPS W -
Movement Pruning: Adaptive Sparsity by Fine-Tuning NeurIPS W PyTorch(Author)
Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot NeurIPS W PyTorch(Author)
Neuron Merging: Compensating for Pruned Neurons NeurIPS F PyTorch(Author)
Neuron-level Structured Pruning using Polarization Regularizer NeurIPS F PyTorch(Author)
SCOP: Scientific Control for Reliable Neural Network Pruning NeurIPS F -
Storage Efficient and Dynamic Flexible Runtime Channel Pruning via Deep Reinforcement Learning NeurIPS F -
The Generalization-Stability Tradeoff In Neural Network Pruning NeurIPS F PyTorch(Author)
Pruning Filter in Filter NeurIPS Other PyTorch(Author)
Position-based Scaled Gradient for Model Quantization and Pruning NeurIPS Other PyTorch(Author)
Bayesian Bits: Unifying Quantization and Pruning NeurIPS Other -
Pruning neural networks without any data by iteratively conserving synaptic flow NeurIPS Other PyTorch(Author)
EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning ECCV (Oral) F PyTorch(Author)
DSA: More Efficient Budgeted Pruning via Differentiable Sparsity Allocation ECCV F -
DHP: Differentiable Meta Pruning via HyperNetworks ECCV F PyTorch(Author)
Meta-Learning with Network Pruning ECCV W -
Accelerating CNN Training by Pruning Activation Gradients ECCV W -
DA-NAS: Data Adapted Pruning for Efficient Neural Architecture Search ECCV Other -
Differentiable Joint Pruning and Quantization for Hardware Efficiency ECCV Other -
Channel Pruning via Automatic Structure Search IJCAI F PyTorch(Author)
Adversarial Neural Pruning with Latent Vulnerability Suppression ICML W -
Proving the Lottery Ticket Hypothesis: Pruning is All You Need ICML W -
Soft Threshold Weight Reparameterization for Learnable Sparsity ICML WF Pytorch(Author)
Network Pruning by Greedy Subnetwork Selection ICML F -
Operation-Aware Soft Channel Pruning using Differentiable Masks ICML F -
DropNet: Reducing Neural Network Complexity via Iterative Pruning ICML F -
Towards Efficient Model Compression via Learned Global Ranking CVPR (Oral) F Pytorch(Author)
HRank: Filter Pruning using High-Rank Feature Map CVPR (Oral) F Pytorch(Author)
Neural Network Pruning with Residual-Connections and Limited-Data CVPR (Oral) F -
Multi-Dimensional Pruning: A Unified Framework for Model Compression CVPR (Oral) WF -
DMCP: Differentiable Markov Channel Pruning for Neural Networks CVPR (Oral) F TensorFlow(Author)
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression CVPR F PyTorch(Author)
Few Sample Knowledge Distillation for Efficient Network Compression CVPR F -
Discrete Model Compression With Resource Constraint for Deep Neural Networks CVPR F -
Structured Compression by Weight Encryption for Unstructured Pruning and Quantization CVPR W -
Learning Filter Pruning Criteria for Deep Convolutional Neural Networks Acceleration CVPR F -
APQ: Joint Search for Network Architecture, Pruning and Quantization Policy CVPR F -
Comparing Rewinding and Fine-tuning in Neural Network Pruning ICLR (Oral) WF TensorFlow(Author)
A Signal Propagation Perspective for Pruning Neural Networks at Initialization ICLR (Spotlight) W -
ProxSGD: Training Structured Neural Networks under Regularization and Constraints ICLR W TF+PT(Author)
One-Shot Pruning of Recurrent Neural Networks by Jacobian Spectrum Evaluation ICLR W -
Lookahead: A Far-sighted Alternative of Magnitude-based Pruning ICLR W PyTorch(Author)
Dynamic Model Pruning with Feedback ICLR WF -
Provable Filter Pruning for Efficient Neural Networks ICLR F -
Data-Independent Neural Pruning via Coresets ICLR W -
AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates AAAI F -
DARB: A Density-Aware Regular-Block Pruning for Deep Neural Networks AAAI Other -
Pruning from Scratch AAAI Other -

2019

Title Venue Type Code
Network Pruning via Transformable Architecture Search NeurIPS F PyTorch(Author)
Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks NeurIPS F PyTorch(Author)
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask NeurIPS W TensorFlow(Author)
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers NeurIPS W -
Global Sparse Momentum SGD for Pruning Very Deep Neural Networks NeurIPS W PyTorch(Author)
AutoPrune: Automatic Network Pruning by Regularizing Auxiliary Parameters NeurIPS W -
Model Compression with Adversarial Robustness: A Unified Optimization Framework NeurIPS Other PyTorch(Author)
MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning ICCV F PyTorch(Author)
Accelerate CNN via Recursive Bayesian Pruning ICCV F -
Adversarial Robustness vs Model Compression, or Both? ICCV W PyTorch(Author)
Learning Filter Basis for Convolutional Neural Network Compression ICCV Other -
Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration CVPR (Oral) F PyTorch(Author)
Towards Optimal Structured CNN Pruning via Generative Adversarial Learning CVPR F PyTorch(Author)
Centripetal SGD for Pruning Very Deep Convolutional Networks with Complicated Structure CVPR F PyTorch(Author)
On Implicit Filter Level Sparsity in Convolutional Neural Networks, Extension1, Extension2 CVPR F PyTorch(Author)
Structured Pruning of Neural Networks with Budget-Aware Regularization CVPR F -
Importance Estimation for Neural Network Pruning CVPR F PyTorch(Author)
OICSR: Out-In-Channel Sparsity Regularization for Compact Deep Neural Networks CVPR F -
Partial Order Pruning: for Best Speed/Accuracy Trade-off in Neural Architecture Search CVPR Other TensorFlow(Author)
Variational Convolutional Neural Network Pruning CVPR - -
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks ICLR (Best) W TensorFlow(Author)
Rethinking the Value of Network Pruning ICLR F PyTorch(Author)
Dynamic Channel Pruning: Feature Boosting and Suppression ICLR F TensorFlow(Author)
SNIP: Single-shot Network Pruning based on Connection Sensitivity ICLR W TensorFLow(Author)
Dynamic Sparse Graph for Efficient Deep Learning ICLR F CUDA(3rd)
Collaborative Channel Pruning for Deep Networks ICML F -
Approximated Oracle Filter Pruning for Destructive CNN Width Optimization github ICML F -
EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis4 ICML W PyTorch(Author)
COP: Customized Deep Model Compression via Regularized Correlation-Based Filter-Level Pruning IJCAI F Tensorflow(Author)

2018

Title Venue Type Code
Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolution Layers ICLR F TensorFlow(Author), PyTorch(3rd)
To prune, or not to prune: exploring the efficacy of pruning for model compression ICLR W -
Discrimination-aware Channel Pruning for Deep Neural Networks NeurIPS F TensorFlow(Author)
Frequency-Domain Dynamic Pruning for Convolutional Neural Networks NeurIPS W -
Learning Sparse Neural Networks via Sensitivity-Driven Regularization NeurIPS WF -
Amc: Automl for model compression and acceleration on mobile devices ECCV F TensorFlow(3rd)
Data-Driven Sparse Structure Selection for Deep Neural Networks ECCV F MXNet(Author)
Coreset-Based Neural Network Compression ECCV F PyTorch(Author)
Constraint-Aware Deep Neural Network Compression ECCV W SkimCaffe(Author)
A Systematic DNN Weight Pruning Framework using Alternating Direction Method of Multipliers ECCV W Caffe(Author)
PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning CVPR F PyTorch(Author)
NISP: Pruning Networks using Neuron Importance Score Propagation CVPR F -
CLIP-Q: Deep Network Compression Learning by In-Parallel Pruning-Quantization CVPR W -
“Learning-Compression” Algorithms for Neural Net Pruning CVPR W -
Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks IJCAI F PyTorch(Author)
Accelerating Convolutional Networks via Global & Dynamic Filter Pruning IJCAI F -

2017

Title Venue Type Code
Pruning Filters for Efficient ConvNets ICLR F PyTorch(3rd)
Pruning Convolutional Neural Networks for Resource Efficient Inference ICLR F TensorFlow(3rd)
Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee NeurIPS W TensorFlow(Author)
Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon NeurIPS W PyTorch(Author)
Runtime Neural Pruning NeurIPS F -
Designing Energy-Efficient Convolutional Neural Networks using Energy-Aware Pruning CVPR F -
ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression ICCV F Caffe(Author), PyTorch(3rd)
Channel pruning for accelerating very deep neural networks ICCV F Caffe(Author)
Learning Efficient Convolutional Networks Through Network Slimming ICCV F PyTorch(Author)

2016

Title Venue Type Code
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding ICLR (Best) W Caffe(Author)
Dynamic Network Surgery for Efficient DNNs NeurIPS W Caffe(Author)

2015

Title Venue Type Code
Learning both Weights and Connections for Efficient Neural Networks NeurIPS W PyTorch(3rd)

Related Repo

Awesome-model-compression-and-acceleration

EfficientDNNs

Embedded-Neural-Network

awesome-AutoML-and-Lightweight-Models

Model-Compression-Papers

knowledge-distillation-papers

Network-Speed-and-Compression

Owner
Yang He
Ph.D. student at UTS
Yang He
Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking)

Overview This repository implemented some common motion planners used on autonomous vehicles, including Hybrid A* Planner Frenet Optimal Trajectory Hi

Huiming Zhou 1k Jan 09, 2023
Can we visualize a large scientific data set with a surrogate model? We're building a GAN for the Earth's Mantle Convection data set to see if we can!

EarthGAN - Earth Mantle Surrogate Modeling Can a surrogate model of the Earth’s Mantle Convection data set be built such that it can be readily run in

Tim 0 Dec 09, 2021
This repository contains the code for the paper "Hierarchical Motion Understanding via Motion Programs"

Hierarchical Motion Understanding via Motion Programs (CVPR 2021) This repository contains the official implementation of: Hierarchical Motion Underst

Sumith Kulal 40 Dec 05, 2022
PyTorch implementation of ARM-Net: Adaptive Relation Modeling Network for Structured Data.

A ready-to-use framework of latest models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, and etc.

48 Nov 30, 2022
Look Closer: Bridging Egocentric and Third-Person Views with Transformers for Robotic Manipulation

Look Closer: Bridging Egocentric and Third-Person Views with Transformers for Robotic Manipulation Official PyTorch implementation for the paper Look

Rishabh Jangir 20 Nov 24, 2022
[IEEE TPAMI21] MobileSal: Extremely Efficient RGB-D Salient Object Detection [PyTorch & Jittor]

MobileSal IEEE TPAMI 2021: MobileSal: Extremely Efficient RGB-D Salient Object Detection This repository contains full training & testing code, and pr

Yu-Huan Wu 52 Jan 06, 2023
Code for the bachelors-thesis flaky fault localization

Flaky_Fault_Localization Scripts for the Bachelors-Thesis: "Flaky Fault Localization" by Christian Kasberger. The thesis examines the usefulness of sp

Christian Kasberger 1 Oct 26, 2021
I-BERT: Integer-only BERT Quantization

I-BERT: Integer-only BERT Quantization HuggingFace Implementation I-BERT is also available in the master branch of HuggingFace! Visit the following li

Sehoon Kim 139 Dec 27, 2022
[TIP 2021] SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction

SADRNet Paper link: SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction Requirements python

Multimedia Computing Group, Nanjing University 99 Dec 30, 2022
This is the official implementation of the paper "Object Propagation via Inter-Frame Attentions for Temporally Stable Video Instance Segmentation".

[CVPRW 2021] - Object Propagation via Inter-Frame Attentions for Temporally Stable Video Instance Segmentation

Anirudh S Chakravarthy 6 May 03, 2022
Python calculations for the position of the sun and moon.

Astral This is 'astral' a Python module which calculates Times for various positions of the sun: dawn, sunrise, solar noon, sunset, dusk, solar elevat

Simon Kennedy 169 Dec 20, 2022
FairyTailor: Multimodal Generative Framework for Storytelling

FairyTailor: Multimodal Generative Framework for Storytelling

Eden Bens 172 Dec 30, 2022
Python library to receive live stream events like comments and gifts in realtime from TikTok LIVE.

TikTokLive A python library to connect to and read events from TikTok's LIVE service A python library to receive and decode livestream events such as

Isaac Kogan 277 Dec 23, 2022
wlad 2 Dec 19, 2022
An attempt at the implementation of GLOM, Geoffrey Hinton's paper for emergent part-whole hierarchies from data

GLOM TensorFlow This Python package attempts to implement GLOM in TensorFlow, which allows advances made by several different groups transformers, neu

Rishit Dagli 32 Feb 21, 2022
Easy Parallel Library (EPL) is a general and efficient deep learning framework for distributed model training.

English | 简体中文 Easy Parallel Library Overview Easy Parallel Library (EPL) is a general and efficient library for distributed model training. Usability

Alibaba 185 Dec 21, 2022
Implementation of Bottleneck Transformer in Pytorch

Bottleneck Transformer - Pytorch Implementation of Bottleneck Transformer, SotA visual recognition model with convolution + attention that outperforms

Phil Wang 621 Jan 06, 2023
Official code of Team Yao at Multi-Modal-Fact-Verification-2022

Official code of Team Yao at Multi-Modal-Fact-Verification-2022 A Multi-Modal Fact Verification dataset released as part of the De-Factify workshop in

Wei-Yao Wang 11 Nov 15, 2022
Implementation of Kronecker Attention in Pytorch

Kronecker Attention Pytorch Implementation of Kronecker Attention in Pytorch. Results look less than stellar, but if someone found some context where

Phil Wang 16 May 06, 2022
A Confidence-based Iterative Solver of Depths and Surface Normals for Deep Multi-view Stereo

idn-solver Paper | Project Page This repository contains the code release of our ICCV 2021 paper: A Confidence-based Iterative Solver of Depths and Su

zhaowang 43 Nov 17, 2022