Alternatives and similar repositories for natural-gradients

Users that are interested in natural-gradients are comparing it to the libraries listed below

• ruosongwang / CNTK
  Convolutional Neural Tangent Kernel
  ☆112Updated 6 years ago
• mariogeiger / hessian
  hessian in pytorch
  ☆187Updated 5 years ago
• fwcore / mean-field-theory-deep-learning
  paper lists and information on mean-field theory of deep learning
  ☆78Updated 6 years ago
• Thrandis / EKFAC-pytorch
  Repository containing Pytorch code for EKFAC and K-FAC perconditioners.
  ☆148Updated 2 years ago
• gbaydin / hypergradient-descent
  Hypergradient descent
  ☆147Updated last year
• damaru2 / ntk
  NTK reading group
  ☆87Updated 6 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆101Updated 7 years ago
• prolearner / hypertorch
  ☆125Updated last year
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆49Updated 9 months ago
• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆50Updated 7 years ago
• djstrouse / information-bottleneck
  a python implementation of various versions of the information bottleneck, including automated parameter searching
  ☆129Updated 5 years ago
• google / spectral-density
  Hessian spectral density estimation in TF and Jax
  ☆124Updated 5 years ago
• yaroslavvb / kfac_pytorch
  ☆134Updated 8 years ago
• bobby-he / Neural_Tangent_Kernel
  ☆68Updated 6 years ago
• revbucket / geometric-certificates
  Geometric Certifications of Neural Nets
  ☆42Updated 3 years ago
• ganguli-lab / deepchaos
  Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"
  ☆73Updated 9 years ago
• emtiyaz / vadam
  Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …
  ☆112Updated 6 years ago
• google-deepmind / mc_gradients
  ☆172Updated last year
• gknilsen / pyhessian
  pyhessian is a TensorFlow module which can be used to estimate Hessian matrices
  ☆25Updated 4 years ago
• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆132Updated 6 years ago
• cybertronai / pytorch-sso
  PyTorch-SSO: Scalable Second-Order methods in PyTorch
  ☆148Updated 2 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆42Updated 3 years ago
• fKunstner / fast-individual-gradients-with-autodiff
  ☆26Updated 6 years ago
• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆66Updated 5 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆49Updated 5 years ago
• duvenaud / relax
  Optimizing control variates for black-box gradient estimation
  ☆163Updated 6 years ago
• thjashin / spectral-stein-grad
  Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)
  ☆34Updated 2 years ago
• mmrl / disent-and-gen
  Code from the article: "The Role of Disentanglement in Generalisation" (ICLR, 2021).
  ☆22Updated 3 years ago
• ruqizhang / csgmcmc
  Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
  ☆93Updated 5 years ago
• thegregyang / NTK4A
  Code for the paper: "Tensor Programs II: Neural Tangent Kernel for Any Architecture"
  ☆106Updated 5 years ago