cybertronai / pytorch-sso

Related projects ⓘ

Alternatives and complementary repositories for pytorch-sso

• AlexanderMath / fasth
  Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.
  ☆69Updated 3 months ago
• google / spectral-density
  Hessian spectral density estimation in TF and Jax
  ☆115Updated 4 years ago
• gbaydin / hypergradient-descent
  Hypergradient descent
  ☆138Updated 5 months ago
• cybertronai / autograd-lib
  ☆33Updated 4 years ago
• cybertronai / autograd-hacks
  ☆153Updated 2 years ago
• fmeirinhos / pytorch-hessianfree
  PyTorch implementation of Hessian Free optimisation
  ☆43Updated 4 years ago
• riannevdberg / sylvester-flows
  ☆178Updated 5 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆80Updated 4 years ago
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆45Updated 4 years ago
• nicola-decao / BNAF
  Pytorch implementation of Block Neural Autoregressive Flow
  ☆176Updated 3 years ago
• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆131Updated 4 years ago
• kazukiosawa / asdl
  ASDL: Automatic Second-order Differentiation Library for PyTorch
  ☆179Updated 3 months ago
• lezcano / expRNN
  Optimization with orthogonal constraints and on general manifolds
  ☆126Updated 4 years ago
• google-deepmind / mc_gradients
  ☆159Updated 3 months ago
• Thrandis / EKFAC-pytorch
  Repository containing Pytorch code for EKFAC and K-FAC perconditioners.
  ☆140Updated last year
• team-approx-bayes / dl-with-bayes
  Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"
  ☆242Updated 4 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 4 years ago
• g-benton / loss-surface-simplexes
  ☆97Updated 2 years ago
• mariogeiger / hessian
  hessian in pytorch
  ☆186Updated 4 years ago
• ruqizhang / csgmcmc
  Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
  ☆92Updated 4 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• alecwangcq / KFAC-Pytorch
  Pytorch implementation of KFAC and E-KFAC (Natural Gradient).
  ☆128Updated 5 years ago
• TrentBrick / PyTorchDiscreteFlows
  Discrete Normalizing Flows implemented in PyTorch
  ☆107Updated 3 years ago
• modestyachts / neural_kernels_code
  ☆36Updated 3 years ago
• senya-ashukha / real-nvp-pytorch
  Real NVP PyTorch a Minimal Working Example | Normalizing Flow
  ☆137Updated 4 years ago
• ruosongwang / CNTK
  Convolutional Neural Tangent Kernel
  ☆107Updated 5 years ago
• prolearner / hypertorch
  ☆119Updated 5 months ago
• microsoft / bayesianize
  Bayesianize: A Bayesian neural network wrapper in pytorch
  ☆87Updated 6 months ago
• bobby-he / Neural_Tangent_Kernel
  ☆67Updated 5 years ago
• thjashin / spectral-stein-grad
  Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)
  ☆32Updated last year