AMLab-Amsterdam / L0_regularization
Learning Sparse Neural Networks through L0 regularization
☆239Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for L0_regularization
- an implementation of L0 regularization with PyTorch☆56Updated 6 years ago
- Mode Connectivity and Fast Geometric Ensembles in PyTorch☆265Updated 2 years ago
- ☆153Updated 2 years ago
- SNIP: SINGLE-SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY☆111Updated 5 years ago
- Pytorch implementation of the paper "SNIP: Single-shot Network Pruning based on Connection Sensitivity" by Lee et al.☆105Updated 5 years ago
- Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH☆101Updated 4 years ago
- A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).☆205Updated 5 years ago
- [ICML 2018] "Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions"☆150Updated 2 years ago
- ☆119Updated 5 months ago
- Implementation of soft parameter sharing for neural networks☆69Updated 3 years ago
- PyTorch code for training neural networks without global back-propagation☆162Updated 5 years ago
- Codes for Layer-wise Optimal Brain Surgeon☆75Updated 5 years ago
- Efficient PyTorch Hessian eigendecomposition tools!☆364Updated 8 months ago
- Sparse Variational Dropout, ICML 2017☆310Updated 4 years ago
- ☆143Updated last year
- Implementation of Continuous Sparsification, a method for pruning and ticket search in deep networks☆32Updated 2 years ago
- Soft Threshold Weight Reparameterization for Learnable Sparsity☆88Updated last year
- PyTorch implementation of [1412.6553] and [1511.06530] tensor decomposition methods for convolutional layers.☆279Updated 2 years ago
- Reproduction and analysis of SNIP paper☆29Updated 4 years ago
- Code release for paper "Random Search and Reproducibility for NAS"☆167Updated 5 years ago
- This repository is no longer maintained. Check☆82Updated 4 years ago
- [ICLR 2020] NAS evaluation is frustratingly hard☆149Updated last year
- Implements quantized distillation. Code for our paper "Model compression via distillation and quantization"☆329Updated 3 months ago
- This repository contains code to replicate the experiments given in NeurIPS 2019 paper "One ticket to win them all: generalizing lottery …☆51Updated 3 months ago
- ☆82Updated 4 years ago
- ☆219Updated 3 months ago
- PyTorch Implementations of Dropout Variants☆87Updated 6 years ago
- Neural Architecture Search with Bayesian Optimisation and Optimal Transport☆133Updated 5 years ago
- Lua implementation of Entropy-SGD☆81Updated 6 years ago
- A Re-implementation of Fixed-update Initialization☆151Updated 5 years ago