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
Face Recognition Attendance Project

Face-Recognition-Attendance-Project In This Project You will learn how to mark attendance using face recognition, Hello Guys This is Gautam Kumar, Thi

Gautam Kumar 1 Dec 03, 2022
Cave Generation using metaballs in Blender. Originally created by sdfgeoff, Edited by Myself (Archie Jaskowicz).

Blender-Cave-Generation Cave Generation using metaballs in Blender. Originally created by sdfgeoff, Edited by Myself (Archie Jaskowicz). Installation

2 Dec 28, 2022
The codes and related files to reproduce the results for Image Similarity Challenge Track 1.

ISC-Track1-Submission The codes and related files to reproduce the results for Image Similarity Challenge Track 1. Required dependencies To begin with

Wenhao Wang 115 Jan 02, 2023
LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION

Query Selector Here you can find code and data loaders for the paper https://arxiv.org/pdf/2107.08687v1.pdf . Query Selector is a novel approach to sp

MORAI 62 Dec 17, 2022
The Illinois repository for Climatehack (https://climatehack.ai/). We won 1st place!

Climatehack This is the repository for Illinois's Climatehack Team. We earned first place on the leaderboard with a final score of 0.87992. An overvie

Jatin Mathur 20 Jun 09, 2022
FAST Aiming at the problems of cumbersome steps and slow download speed of GNSS data

FAST Aiming at the problems of cumbersome steps and slow download speed of GNSS data, a relatively complete set of integrated multi-source data download terminal software fast is developed. The softw

ChangChuntao 23 Dec 31, 2022
Conservative Q Learning for Offline Reinforcement Reinforcement Learning in JAX

CQL-JAX This repository implements Conservative Q Learning for Offline Reinforcement Reinforcement Learning in JAX (FLAX). Implementation is built on

Karush Suri 8 Nov 07, 2022
This is a collection of our NAS and Vision Transformer work.

AutoML - Neural Architecture Search This is a collection of our AutoML-NAS work iRPE (NEW): Rethinking and Improving Relative Position Encoding for Vi

Microsoft 832 Jan 08, 2023
This repository is the official implementation of the Hybrid Self-Attention NEAT algorithm.

This repository is the official implementation of the Hybrid Self-Attention NEAT algorithm. It contains the code to reproduce the results presented in the original paper: https://arxiv.org/abs/2112.0

Saman Khamesian 6 Dec 13, 2022
Python package for downloading ECMWF reanalysis data and converting it into a time series format.

ecmwf_models Readers and converters for data from the ECMWF reanalysis models. Written in Python. Works great in combination with pytesmo. Citation If

TU Wien - Department of Geodesy and Geoinformation 31 Dec 26, 2022
RealTime Emotion Recognizer for Machine Learning Study Jam's demo

Emotion recognizer Table of contents Clone project Dataset Install dependencies Main program Demo 1. Clone project git clone https://github.com/GDSC20

Google Developer Student Club - UIT 1 Oct 05, 2021
ReLoss - Official implementation for paper "Relational Surrogate Loss Learning" ICLR 2022

Relational Surrogate Loss Learning (ReLoss) Official implementation for paper "R

Tao Huang 31 Nov 22, 2022
The sixth place winning solution (6/220) in 2021 Gaofen Challenge.

SwinTransformer + OBBDet The sixth place winning solution (6/220) in the track of Fine-grained Object Recognition in High-Resolution Optical Images, 2

ming71 46 Dec 02, 2022
Federated Deep Reinforcement Learning for the Distributed Control of NextG Wireless Networks.

FDRL-PC-Dyspan Federated Deep Reinforcement Learning for the Distributed Control of NextG Wireless Networks. This repository contains the entire code

Peyman Tehrani 17 Nov 18, 2022
A collection of loss functions for medical image segmentation

A collection of loss functions for medical image segmentation

Jun 3.1k Jan 03, 2023
Like ThreeJS but for Python and based on wgpu

pygfx A render engine, inspired by ThreeJS, but for Python and targeting Vulkan/Metal/DX12 (via wgpu). Introduction This is a Python render engine bui

139 Jan 07, 2023
Official implementation of the ICCV 2021 paper "Conditional DETR for Fast Training Convergence".

The DETR approach applies the transformer encoder and decoder architecture to object detection and achieves promising performance. In this paper, we handle the critical issue, slow training convergen

281 Dec 30, 2022
A developer interface for creating Chat AIs for the Chai app.

ChaiPy A developer interface for creating Chat AIs for the Chai app. Usage Local development A quick start guide is available here, with a minimal exa

Chai 28 Dec 28, 2022
Python3 / PyTorch implementation of the following paper: Fine-grained Semantics-aware Representation Enhancement for Self-supervisedMonocular Depth Estimation. ICCV 2021 (oral)

FSRE-Depth This is a Python3 / PyTorch implementation of FSRE-Depth, as described in the following paper: Fine-grained Semantics-aware Representation

77 Dec 28, 2022
Inference pipeline for our participation in the FeTA challenge 2021.

feta-inference Inference pipeline for our participation in the FeTA challenge 2021. Team name: TRABIT Installation Download the two folders in https:/

Lucas Fidon 2 Apr 13, 2022