uber-research / deconstructing-lottery-ticketsLinks
☆144Updated 2 years ago
Alternatives and similar repositories for deconstructing-lottery-tickets
Users that are interested in deconstructing-lottery-tickets are comparing it to the libraries listed below
Sorting:
- ☆193Updated 4 years ago
- End-to-end training of sparse deep neural networks with little-to-no performance loss.☆326Updated 2 years ago
- Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH☆106Updated 5 years ago
- Discovering Neural Wirings (https://arxiv.org/abs/1906.00586)☆137Updated 5 years ago
- ☆227Updated last year
- [ICLR 2020] Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks☆139Updated 4 years ago
- ☆83Updated 5 years ago
- 🧀 Pytorch code for the Fromage optimiser.☆128Updated last year
- Mode Connectivity and Fast Geometric Ensembles in PyTorch☆277Updated 2 years ago
- SNIP: SINGLE-SHOT NETWORK PRUNING☆31Updated 6 months ago
- Code for "EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis" https://arxiv.org/abs/1905.05934☆113Updated 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 last year
- A Re-implementation of Fixed-update Initialization☆155Updated 6 years ago
- Code for "Supermasks in Superposition"☆124Updated 2 years ago
- Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".☆62Updated 6 years ago
- Efficient PyTorch Hessian eigendecomposition tools!☆379Updated last year
- Implementation for the Lookahead Optimizer.☆243Updated 3 years ago
- This repository is no longer maintained. Check☆81Updated 5 years ago
- SNIP: SINGLE-SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY☆115Updated 6 years ago
- A drop-in replacement for CIFAR-10.☆246Updated 4 years ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆147Updated 2 years ago
- PyTorch code for training neural networks without global back-propagation☆165Updated 5 years ago
- This repository contains the results for the paper: "Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers"☆184Updated 4 years ago
- Learning Sparse Neural Networks through L0 regularization☆244Updated 5 years ago
- ☆133Updated 4 years ago
- ☆70Updated 5 years ago
- Memory efficient MAML using gradient checkpointing☆86Updated 5 years ago
- NTK reading group☆87Updated 5 years ago
- "Layer-wise Adaptive Rate Scaling" in PyTorch☆87Updated 4 years ago