tyohei / chainerkfacLinks
A Chainer extension for K-FAC
☆20Updated 6 years ago
Alternatives and similar repositories for chainerkfac
Users that are interested in chainerkfac are comparing it to the libraries listed below
Sorting:
- Limitations of the Empirical Fisher Approximation☆49Updated 9 months ago
- ☆83Updated 5 years ago
- This repository is no longer maintained. Check☆81Updated 5 years ago
- Lua implementation of Entropy-SGD☆81Updated 7 years ago
- Repository containing Pytorch code for EKFAC and K-FAC perconditioners.☆149Updated 2 years ago
- hessian in pytorch☆187Updated 5 years ago
- Regularization, Neural Network Training Dynamics☆14Updated 5 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆35Updated 5 years ago
- Collection of algorithms for approximating Fisher Information Matrix for Natural Gradient (and second order method in general)☆142Updated 6 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Pytorch implementation of KFAC and E-KFAC (Natural Gradient).☆132Updated 6 years ago
- ☆27Updated 7 years ago
- Optimization with orthogonal constraints and on general manifolds☆130Updated 5 years ago
- Code for "Accelerating Natural Gradient with Higher-Order Invariance"☆30Updated 6 years ago
- Monotone operator equilibrium networks☆54Updated 5 years ago
- Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".☆62Updated 6 years ago
- ☆47Updated 6 years ago
- Convolutional Neural Tangent Kernel☆112Updated 6 years ago
- Implementation of the Deep Frank-Wolfe Algorithm -- Pytorch☆63Updated 4 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆58Updated 6 years ago
- ☆26Updated 6 years ago
- The Full Spectrum of Deepnet Hessians at Scale: Dynamics with SGD Training and Sample Size☆17Updated 6 years ago
- ☆77Updated 6 years ago
- Geometric Certifications of Neural Nets☆42Updated 3 years ago
- Code for "EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis" https://arxiv.org/abs/1905.05934☆113Updated 5 years ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆148Updated 2 years ago
- PyTorch AutoNEB implementation to identify minimum energy paths, e.g. in neural network loss landscapes☆56Updated 3 years ago
- ☆134Updated 8 years ago
- SGD and Ordered SGD codes for deep learning, SVM, and logistic regression☆36Updated 5 years ago
- PyTorch implementation of FIM and empirical FIM☆60Updated 7 years ago