AMLab-Amsterdam / L0_regularizationLinks
Learning Sparse Neural Networks through L0 regularization
☆241Updated 4 years ago
Alternatives and similar repositories for L0_regularization
Users that are interested in L0_regularization are comparing it to the libraries listed below
Sorting:
- an implementation of L0 regularization with PyTorch☆57Updated 7 years ago
- Mode Connectivity and Fast Geometric Ensembles in PyTorch☆271Updated 2 years ago
- SNIP: SINGLE-SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY☆114Updated 5 years ago
- Compressing Neural Networks using the Variational Information Bottleneck☆66Updated 2 years ago
- Pytorch implementation of the paper "SNIP: Single-shot Network Pruning based on Connection Sensitivity" by Lee et al.☆108Updated 6 years ago
- Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH☆105Updated 5 years ago
- ☆157Updated 3 years ago
- This repository contains code to replicate the experiments given in NeurIPS 2019 paper "One ticket to win them all: generalizing lottery …☆51Updated 11 months ago
- ☆123Updated last year
- ☆83Updated 5 years ago
- Code release for paper "Random Search and Reproducibility for NAS"☆167Updated 5 years ago
- Implements pytorch code for the Accelerated SGD algorithm.☆215Updated 7 years ago
- PyTorch Implementations of Dropout Variants☆87Updated 7 years ago
- A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).☆206Updated 6 years ago
- Implementation of soft parameter sharing for neural networks☆69Updated 4 years ago
- SNIP: SINGLE-SHOT NETWORK PRUNING☆31Updated 3 months ago
- ☆144Updated 2 years ago
- Efficient PyTorch Hessian eigendecomposition tools!☆374Updated last year
- Soft Threshold Weight Reparameterization for Learnable Sparsity☆91Updated 2 years ago
- [ICLR 2020] NAS evaluation is frustratingly hard☆149Updated last year
- Code for paper "Learning to Reweight Examples for Robust Deep Learning"☆269Updated 6 years ago
- Codes for Layer-wise Optimal Brain Surgeon☆78Updated 6 years ago
- hessian in pytorch☆187Updated 4 years ago
- [ICML 2018] "Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions"☆152Updated 3 years ago
- PyTorch code for training neural networks without global back-propagation☆165Updated 5 years ago
- ☆59Updated 2 years ago
- ☆226Updated 11 months ago
- [NeurIPS '18] "Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?" Official Implementation.☆129Updated 3 years ago
- Code for "Stochastic Optimization of Sorting Networks using Continuous Relaxations", ICLR 2019.☆145Updated 2 years ago
- Example code for the paper "Understanding deep learning requires rethinking generalization"☆178Updated 5 years ago