AMLab-Amsterdam / L0_regularizationLinks
Learning Sparse Neural Networks through L0 regularization
☆244Updated 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:
- Mode Connectivity and Fast Geometric Ensembles in PyTorch☆272Updated 2 years ago
- an implementation of L0 regularization with PyTorch☆57Updated 7 years ago
- Efficient PyTorch Hessian eigendecomposition tools!☆374Updated last year
- ☆157Updated 3 years ago
- PyTorch code for training neural networks without global back-propagation☆165Updated 5 years ago
- Compressing Neural Networks using the Variational Information Bottleneck☆66Updated 2 years ago
- SNIP: SINGLE-SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY☆114Updated 6 years ago
- Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH☆105Updated 5 years ago
- ☆59Updated 2 years ago
- ☆83Updated 5 years ago
- ☆144Updated 2 years ago
- A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).☆206Updated 6 years ago
- [NeurIPS '18] "Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?" Official Implementation.☆129Updated 3 years ago
- SNIP: SINGLE-SHOT NETWORK PRUNING☆31Updated 4 months ago
- Example code for the paper "Understanding deep learning requires rethinking generalization"☆178Updated 5 years ago
- MINE: Mutual Information Neural Estimation in pytorch (unofficial)☆204Updated 6 years ago
- NTK reading group☆87Updated 5 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
- ☆226Updated 11 months ago
- [ICML 2018] "Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions"☆152Updated 3 years ago
- Neural Architecture Search with Bayesian Optimisation and Optimal Transport☆134Updated 6 years ago
- ☆123Updated last year
- Pytorch implementation of the paper "SNIP: Single-shot Network Pruning based on Connection Sensitivity" by Lee et al.☆108Updated 6 years ago
- explore DNNs via Infomration☆265Updated 5 years ago
- Gradient based hyperparameter optimization & meta-learning package for TensorFlow☆188Updated 5 years ago
- Code for experiments regarding importance sampling for training neural networks☆329Updated 3 years ago
- hessian in pytorch☆187Updated 4 years ago
- PyTorch Implementations of Dropout Variants☆87Updated 7 years ago
- This project is the Torch implementation of our accepted AAAI 2018 paper : orthogonal weight normalization method for solving orthogonali…☆57Updated 5 years ago
- Implementation of soft parameter sharing for neural networks☆70Updated 4 years ago