facebookresearch / spartanLinks
Spartan is an algorithm for training sparse neural network models. This repository accompanies the paper "Spartan Differentiable Sparsity via Regularized Transportation" (NeurIPS 2022).
☆24Updated 2 years ago
Alternatives and similar repositories for spartan
Users that are interested in spartan are comparing it to the libraries listed below
Sorting:
- Lightweight torch implementation of rigl, a sparse-to-sparse optimizer.☆57Updated 3 years ago
- [ICML2022] Training Your Sparse Neural Network Better with Any Mask. Ajay Jaiswal, Haoyu Ma, Tianlong Chen, ying Ding, and Zhangyang Wang☆29Updated 3 years ago
- Soft Threshold Weight Reparameterization for Learnable Sparsity☆91Updated 2 years ago
- Code accompanying the NeurIPS 2020 paper: WoodFisher (Singh & Alistarh, 2020)☆53Updated 4 years ago
- Code for Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot☆42Updated 4 years ago
- Identify a binary weight or binary weight and activation subnetwork within a randomly initialized network by only pruning and binarizing …☆52Updated 3 years ago
- [ICML 2022] "Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets" by Tianlong Chen, Xuxi Chen, Xiaolong Ma, Yanzhi Wa…☆33Updated 2 years ago
- Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH☆105Updated 5 years ago
- A research library for pytorch-based neural network pruning, compression, and more.☆162Updated 2 years ago
- ☆43Updated last year
- [NeurIPS‘2021] "MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge", Geng Yuan, Xiaolong Ma, Yanzhi Wang et al…☆18Updated 3 years ago
- Code for "Structured Sparsity Inducing Adaptive Optimizers for Deep Learning" in PyTorch☆18Updated 4 years ago
- Factorized Neural Layers☆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…☆28Updated 2 years ago
- ☆10Updated 3 years ago
- ☆19Updated 3 years ago
- Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection☆21Updated 4 years ago
- Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".☆62Updated 6 years ago
- ☆226Updated last year
- ☆70Updated 5 years ago
- DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures☆33Updated 5 years ago
- Hessian trace estimation using PyTorch and Hutch++☆19Updated 4 years ago
- ☆14Updated 4 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
- Prospect Pruning: Finding Trainable Weights at Initialization Using Meta-Gradients☆32Updated 3 years ago
- [IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.☆59Updated last year
- The official code for [ECCV2020] "HALO: Hardware-aware Learning to Optimize"☆10Updated 2 years ago
- Implementation for the paper "Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization"☆74Updated 5 years ago
- ☆213Updated 2 years ago
- [ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, De…☆45Updated last year