stevenygd / SWALP
Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".
☆62Updated 5 years ago
Alternatives and similar repositories for SWALP:
Users that are interested in SWALP 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☆103Updated 5 years ago
- Code for BlockSwap (ICLR 2020).☆33Updated 4 years ago
- DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures☆32Updated 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
- ☆53Updated 6 years ago
- Implementation for the paper "Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization"☆74Updated 5 years ago
- Code for Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot☆42Updated 4 years ago
- Code for the paper "Training Binary Neural Networks with Bayesian Learning Rule☆38Updated 3 years ago
- Implementation of ICLR 2017 paper "Loss-aware Binarization of Deep Networks"☆18Updated 6 years ago
- ☆70Updated 5 years ago
- ☆74Updated 5 years ago
- ☆18Updated 5 years ago
- PyProf2: PyTorch Profiling tool☆82Updated 4 years ago
- Codes for Accepted Paper : "MetaQuant: Learning to Quantize by Learning to Penetrate Non-differentiable Quantization" in NeurIPS 2019☆54Updated 4 years ago
- Soft Threshold Weight Reparameterization for Learnable Sparsity☆89Updated 2 years ago
- ProxQuant: Quantized Neural Networks via Proximal Operators☆29Updated 6 years ago
- PyTorch Code for "Evaluating the search phase of Neural Architecture Search" @ ICLR 2020☆50Updated 5 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
- Proximal Mean-field for Neural Network Quantization☆22Updated 5 years ago
- Code for "EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis" https://arxiv.org/abs/1905.05934☆112Updated 5 years ago
- Successfully training approximations to full-rank matrices for efficiency in deep learning.☆17Updated 4 years ago
- Implementation of ICLR 2018 paper "Loss-aware Weight Quantization of Deep Networks"☆26Updated 5 years ago
- ☆83Updated 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…☆30Updated last year
- ☆62Updated 4 years ago
- This repository is no longer maintained. Check☆81Updated 5 years ago
- All about acceleration and compression of Deep Neural Networks☆33Updated 5 years ago
- Code accompanying the NeurIPS 2020 paper: WoodFisher (Singh & Alistarh, 2020)☆49Updated 4 years ago
- ☆23Updated 6 years ago
- "Layer-wise Adaptive Rate Scaling" in PyTorch☆86Updated 4 years ago