gfrogat / prunhild
A small library implementing magnitude-based pruning in PyTorch
☆28Updated 5 years ago
Related projects ⓘ
Alternatives and complementary repositories for prunhild
- ☆143Updated last year
- This repository is no longer maintained. Check☆82Updated 4 years ago
- 🧀 Pytorch code for the Fromage optimiser.☆122Updated 3 months ago
- Hypergradient descent☆138Updated 5 months ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆53Updated 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 3 months ago
- Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks☆83Updated 2 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆110Updated 5 years ago
- A library for evaluating representations.☆76Updated 2 years ago
- Code for "EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis" https://arxiv.org/abs/1905.05934☆111Updated 4 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆50Updated 7 years ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆141Updated last year
- ☆82Updated 4 years ago
- Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH☆100Updated 4 years ago
- DeepOBS: A Deep Learning Optimizer Benchmark Suite☆103Updated 10 months ago
- An implementation of shampoo☆74Updated 6 years ago
- A Re-implementation of Fixed-update Initialization☆151Updated 5 years ago
- Codebase for Learning Invariances in Neural Networks☆94Updated 2 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 5 years ago
- ☆153Updated 2 years ago
- an implementation of L0 regularization with PyTorch☆56Updated 6 years ago
- The Singular Values of Convolutional Layers☆71Updated 6 years ago
- PyTorch AutoNEB implementation to identify minimum energy paths, e.g. in neural network loss landscapes☆54Updated 2 years ago
- Reproduction and analysis of SNIP paper☆28Updated 4 years ago
- Limitations of the Empirical Fisher Approximation☆45Updated 4 years ago
- [ICLR 2020] Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks☆137Updated 4 years ago
- ☆132Updated 7 years ago
- [NeurIPS 2019] Deep Set Prediction Networks☆100Updated 4 years ago
- TBA☆75Updated 5 years ago
- ☆15Updated 4 years ago