lolemacs / continuous-sparsification
Implementation of Continuous Sparsification, a method for pruning and ticket search in deep networks
☆32Updated 2 years ago
Alternatives and similar repositories for continuous-sparsification:
Users that are interested in continuous-sparsification are comparing it to the libraries listed below
- Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH☆102Updated 4 years ago
- [ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, De…☆46Updated last year
- Code accompanying the NeurIPS 2020 paper: WoodFisher (Singh & Alistarh, 2020)☆47Updated 3 years ago
- Soft Threshold Weight Reparameterization for Learnable Sparsity☆88Updated last year
- [ICML2022] Training Your Sparse Neural Network Better with Any Mask. Ajay Jaiswal, Haoyu Ma, Tianlong Chen, ying Ding, and Zhangyang Wang☆27Updated 2 years ago
- ☆30Updated 2 years ago
- Prospect Pruning: Finding Trainable Weights at Initialization Using Meta-Gradients☆31Updated 2 years ago
- [IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.☆57Updated last year
- [ICLR-2020] Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers.☆31Updated 4 years ago
- ☆33Updated 2 years ago
- ☆57Updated last year
- Reproducing RigL (ICML 2020) as a part of ML Reproducibility Challenge 2020☆27Updated 3 years ago
- Implementation of Effective Sparsification of Neural Networks with Global Sparsity Constraint☆28Updated 2 years ago
- A generic code base for neural network pruning, especially for pruning at initialization.☆30Updated 2 years ago
- Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection☆21Updated 3 years ago
- Pytorch implementation of the paper "SNIP: Single-shot Network Pruning based on Connection Sensitivity" by Lee et al.☆106Updated 5 years ago
- Code for Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot☆42Updated 4 years ago
- ☆222Updated 5 months ago
- Lightweight torch implementation of rigl, a sparse-to-sparse optimizer.☆56Updated 3 years ago
- [NeurIPS‘2021] "MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge", Geng Yuan, Xiaolong Ma, Yanzhi Wang et al…☆18Updated 2 years ago
- Code for our ICLR'2021 paper "DrNAS: Dirichlet Neural Architecture Search"☆44Updated 3 years ago
- Identify a binary weight or binary weight and activation subnetwork within a randomly initialized network by only pruning and binarizing …☆49Updated 2 years ago
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆35Updated 2 years ago
- Reproduction and analysis of SNIP paper☆30Updated 5 years ago
- SNIP: SINGLE-SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY☆112Updated 5 years ago
- [Neurips 2021] Sparse Training via Boosting Pruning Plasticity with Neuroregeneration☆31Updated last year
- ☆14Updated 3 years ago
- Weight-Averaged Sharpness-Aware Minimization (NeurIPS 2022)☆28Updated 2 years ago
- [ICLR 2022] "Learning Pruning-Friendly Networks via Frank-Wolfe: One-Shot, Any-Sparsity, and No Retraining" by Lu Miao*, Xiaolong Luo*, T…☆29Updated 2 years ago
- [ICLR 2023] "Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!" Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen…☆27Updated last year