gpauloski / kfac-pytorchLinks
Distributed K-FAC preconditioner for PyTorch
☆90Updated this week
Alternatives and similar repositories for kfac-pytorch
Users that are interested in kfac-pytorch are comparing it to the libraries listed below
Sorting:
- Pytorch implementation of KFAC and E-KFAC (Natural Gradient).☆132Updated 6 years ago
- Efficient Riemannian Optimization on Stiefel Manifold via Cayley Transform☆42Updated 6 years ago
- Pytorch implementation of KFAC - this is a port of https://github.com/tensorflow/kfac/☆26Updated last year
- ASDL: Automatic Second-order Differentiation Library for PyTorch☆189Updated 9 months ago
- Implementation of "Gradients without backpropagation" paper (https://arxiv.org/abs/2202.08587) using functorch☆111Updated 2 years ago
- Butterfly matrix multiplication in PyTorch☆174Updated last year
- Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.☆76Updated last year
- {KFAC,EKFAC,Diagonal,Implicit} Fisher Matrices and finite width NTKs in PyTorch☆215Updated last week
- Limitations of the Empirical Fisher Approximation☆47Updated 6 months ago
- Repository containing Pytorch code for EKFAC and K-FAC perconditioners.☆146Updated 2 years ago
- ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning☆279Updated 2 years ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆147Updated last year
- Code for the paper: "Tensor Programs II: Neural Tangent Kernel for Any Architecture"☆105Updated 5 years ago
- Hessian spectral density estimation in TF and Jax☆124Updated 5 years ago
- Structured matrices for compressing neural networks☆67Updated last year
- ☆30Updated 4 years ago
- ☆70Updated 9 months ago
- ☆67Updated 6 years ago
- Hessian trace estimation using PyTorch and Hutch++☆19Updated 4 years ago
- Create animations for the optimization trajectory of neural nets☆159Updated last year
- ☆233Updated 7 months ago
- [ICLR 2023] Eva: Practical Second-order Optimization with Kronecker-vectorized Approximation☆12Updated 2 years ago
- ☆214Updated 2 years ago
- A custom PyTorch layer that is capable of implementing extremely wide and sparse linear layers efficiently☆51Updated last year
- Code accompanying our paper "Feature Learning in Infinite-Width Neural Networks" (https://arxiv.org/abs/2011.14522)☆62Updated 4 years ago
- Pytorch implementation of preconditioned stochastic gradient descent (Kron and affine preconditioner, low-rank approximation precondition…☆180Updated this week
- ☆36Updated 9 months ago
- Hessian backpropagation (HBP): PyTorch extension of backpropagation for block-diagonal curvature matrix approximations☆20Updated 2 years ago
- ☆47Updated 6 years ago
- TensorLy-Torch: Deep Tensor Learning with TensorLy and PyTorch☆80Updated last year