StijnVerdenius / SNIP-it
This repository is the official implementation of the paper Pruning via Iterative Ranking of Sensitivity Statistics and implements novel pruning / compression algorithms for deep learning / neural networks. Amongst others it implements structured pruning before training, its actual parameter shrinking and unstructured before/during training.
☆32Updated last year
Alternatives and similar repositories for SNIP-it
Users that are interested in SNIP-it are comparing it to the libraries listed below
Sorting:
- Lookahead: A Far-sighted Alternative of Magnitude-based Pruning (ICLR 2020)☆33Updated 4 years ago
- Code for paper "Orthogonal Convolutional Neural Networks".☆116Updated 3 years ago
- ☆14Updated 4 years ago
- Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH☆104Updated 5 years ago
- Soft Threshold Weight Reparameterization for Learnable Sparsity☆89Updated 2 years ago
- This repository contains code to replicate the experiments given in NeurIPS 2019 paper "One ticket to win them all: generalizing lottery …☆51Updated 9 months ago
- Lightweight torch implementation of rigl, a sparse-to-sparse optimizer.☆56Updated 3 years ago
- Neuron Merging: Compensating for Pruned Neurons (NeurIPS 2020)☆43Updated 4 years ago
- Train ImageNet *fast* in 500 lines of code with FFCV☆142Updated last year
- Prospect Pruning: Finding Trainable Weights at Initialization Using Meta-Gradients☆31Updated 3 years ago
- Code for Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot☆42Updated 4 years ago
- Code for "Online Learned Continual Compression with Adaptive Quantization Modules"☆27Updated 4 years ago
- DropNet: Reducing Neural Network Complexity via Iterative Pruning (ICML 2020)☆15Updated 4 years ago
- Evaluating AlexNet features at various depths☆39Updated 4 years ago
- [CVPR 2021] "The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models" Tianlong Chen, Jon…☆69Updated 2 years ago
- [NeurIPS'20] GradAug: A New Regularization Method for Deep Neural Networks☆93Updated 4 years ago
- PyTorch implementation of shake-drop regularization☆54Updated 5 years ago
- [NeurIPS '18] "Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?" Official Implementation.☆129Updated 3 years ago
- pytorch implementation of "Contrastive Multiview Coding", "Momentum Contrast for Unsupervised Visual Representation Learning", and "Unsup…☆18Updated 5 years ago
- Differentiable Data Augmentation Library☆123Updated 2 years ago
- A research library for pytorch-based neural network pruning, compression, and more.☆161Updated 2 years ago
- A PyTorch converter for SimCLR checkpoints☆108Updated 4 years ago
- Code accompanying the NeurIPS 2020 paper: WoodFisher (Singh & Alistarh, 2020)☆50Updated 4 years ago
- ☆133Updated 4 years ago
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 4 years ago
- ☆191Updated 4 years ago
- SNIP: SINGLE-SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY☆114Updated 5 years ago
- DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures☆33Updated 4 years ago
- A pytorch implementation of our jacobian regularizer to encourage learning representations more robust to input perturbations.☆126Updated last year
- Compressing Representations for Self-Supervised Learning☆78Updated 4 years ago