spcl / sparsity-in-deep-learningLinks
Bibtex for Sparsity in Deep Learning paper (https://arxiv.org/abs/2102.00554) - open for pull requests
☆45Updated 3 years ago
Alternatives and similar repositories for sparsity-in-deep-learning
Users that are interested in sparsity-in-deep-learning are comparing it to the libraries listed below
Sorting:
- Code for the paper "Training Binary Neural Networks with Bayesian Learning Rule☆39Updated 3 years ago
- ☆52Updated 6 years ago
- Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH☆105Updated 5 years ago
- Code accompanying the NeurIPS 2020 paper: WoodFisher (Singh & Alistarh, 2020)☆52Updated 4 years ago
- Soft Threshold Weight Reparameterization for Learnable Sparsity☆91Updated 2 years ago
- Implementation for the paper "Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization"☆74Updated 5 years ago
- [ICLR 2021 Spotlight] "CPT: Efficient Deep Neural Network Training via Cyclic Precision" by Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yinin…☆31Updated last year
- Identify a binary weight or binary weight and activation subnetwork within a randomly initialized network by only pruning and binarizing …☆52Updated 3 years ago
- ☆70Updated 5 years ago
- [Neurips 2021] Sparse Training via Boosting Pruning Plasticity with Neuroregeneration☆31Updated 2 years ago
- Implementation of Continuous Sparsification, a method for pruning and ticket search in deep networks☆33Updated 3 years ago
- Proximal Mean-field for Neural Network Quantization☆22Updated 5 years ago
- Implementation of BinaryConnect on Pytorch☆39Updated 4 years ago
- Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".☆62Updated 6 years ago
- Code for Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot☆42Updated 4 years ago
- [ICLR 2020] Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks☆138Updated 4 years ago
- ☆83Updated 5 years ago
- Code to implement the experiments in "Post-training Quantization for Neural Networks with Provable Guarantees" by Jinjie Zhang, Yixuan Zh…☆11Updated 2 years ago
- Code for "Structured Sparsity Inducing Adaptive Optimizers for Deep Learning" in PyTorch☆18Updated 4 years ago
- DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures☆33Updated 4 years ago
- This is a PyTorch implementation of the Scalpel. Node pruning for five benchmark networks and SIMD-aware weight pruning for LeNet-300-100…☆41Updated 6 years ago
- Pytorch implementation of the paper "SNIP: Single-shot Network Pruning based on Connection Sensitivity" by Lee et al.☆108Updated 6 years ago
- Lightweight torch implementation of rigl, a sparse-to-sparse optimizer.☆57Updated 3 years ago
- Conditional channel- and precision-pruning on neural networks☆72Updated 5 years ago
- [ICML2022] Training Your Sparse Neural Network Better with Any Mask. Ajay Jaiswal, Haoyu Ma, Tianlong Chen, ying Ding, and Zhangyang Wang☆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…☆30Updated 3 years ago
- A research library for pytorch-based neural network pruning, compression, and more.☆162Updated 2 years ago
- [IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.☆59Updated last year
- Factorized Neural Layers☆29Updated last year
- Reducing the size of convolutional neural networks☆112Updated 7 years ago