Dejiao2018 / GrOWL
Learning to share: simultaneous parameter tying and sparsification in deep learning
☆12Updated 6 years ago
Alternatives and similar repositories for GrOWL:
Users that are interested in GrOWL are comparing it to the libraries listed below
- Combined Group and Exclusive Sparsity for Deep Neural Networks, ICML 2017☆31Updated 7 years ago
- Feasible target propagation code for the paper "Deep Learning as a Mixed Convex-Combinatorial Optimization Problem" by Friesen & Domingos…☆28Updated 7 years ago
- Structured Bayesian Pruning, NIPS 2017☆74Updated 4 years ago
- Code for paper "Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking"☆18Updated 5 years ago
- A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).☆206Updated 6 years ago
- Path-Level Network Transformation for Efficient Architecture Search, in ICML 2018.☆112Updated 6 years ago
- Code for "EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis" https://arxiv.org/abs/1905.05934☆112Updated 5 years ago
- Implementation of the Deep Frank-Wolfe Algorithm -- Pytorch☆62Updated 4 years ago
- ☆83Updated 5 years ago
- Lua implementation of Entropy-SGD☆81Updated 7 years ago
- Implementation of ICLR 2017 paper "Loss-aware Binarization of Deep Networks"☆18Updated 6 years ago
- Compressing Neural Networks using the Variational Information Bottleneck☆66Updated 2 years ago
- Net2Net implementation on PyTorch for any possible vision layers.☆38Updated 7 years ago
- Implementation of soft parameter sharing for neural networks☆69Updated 4 years ago
- ☆27Updated 6 years ago
- Implementation of ICLR 2018 paper "Loss-aware Weight Quantization of Deep Networks"☆26Updated 5 years ago
- This repository is no longer maintained. Check☆81Updated 5 years ago
- ☆33Updated 6 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
- This repository contains the code for our recent paper `Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters'☆21Updated 6 years ago
- A PyTorch implementation of the iterative pruning method described in Han et. al. (2015)☆40Updated 6 years ago
- Pytorch implementation of TRP☆45Updated 4 years ago
- SmoothOut: Smoothing Out Sharp Minima to Improve Generalization in Deep Learning☆23Updated 6 years ago