Alternatives and similar repositories for pytorch-sso:

Users that are interested in pytorch-sso are comparing it to the libraries listed below

• AlexanderMath / fasth
  Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.
  ☆73Updated 7 months ago
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆47Updated 4 years ago
• gbaydin / hypergradient-descent
  Hypergradient descent
  ☆145Updated 9 months ago
• g-benton / loss-surface-simplexes
  ☆98Updated 3 years ago
• cybertronai / autograd-hacks
  ☆156Updated 2 years ago
• Thrandis / EKFAC-pytorch
  Repository containing Pytorch code for EKFAC and K-FAC perconditioners.
  ☆141Updated last year
• lezcano / expRNN
  Optimization with orthogonal constraints and on general manifolds
  ☆127Updated 4 years ago
• google / spectral-density
  Hessian spectral density estimation in TF and Jax
  ☆121Updated 4 years ago
• cybertronai / autograd-lib
  ☆33Updated 4 years ago
• kazukiosawa / asdl
  ASDL: Automatic Second-order Differentiation Library for PyTorch
  ☆183Updated 2 months ago
• mariogeiger / hessian
  hessian in pytorch
  ☆186Updated 4 years ago
• TrentBrick / PyTorchDiscreteFlows
  Discrete Normalizing Flows implemented in PyTorch
  ☆109Updated 3 years ago
• riannevdberg / sylvester-flows
  ☆179Updated 5 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
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• modestyachts / neural_kernels_code
  ☆36Updated 3 years ago
• alecwangcq / KFAC-Pytorch
  Pytorch implementation of KFAC and E-KFAC (Natural Gradient).
  ☆130Updated 5 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆81Updated 4 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• fmeirinhos / pytorch-hessianfree
  PyTorch implementation of Hessian Free optimisation
  ☆43Updated 5 years ago
• nicola-decao / BNAF
  Pytorch implementation of Block Neural Autoregressive Flow
  ☆178Updated 3 years ago
• rtqichen / residual-flows
  code for "Residual Flows for Invertible Generative Modeling".
  ☆265Updated last year
• microsoft / bayesianize
  Bayesianize: A Bayesian neural network wrapper in pytorch
  ☆88Updated 9 months ago
• izmailovpavel / understandingbdl
  ☆238Updated 2 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago
• google-deepmind / mc_gradients
  ☆164Updated 7 months ago
• cunningham-lab / cb_and_cc
  ☆36Updated 2 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆51Updated 4 years ago
• cemanil / LNets
  Lipschitz Neural Networks described in "Sorting Out Lipschitz Function Approximation" (ICML 2019).
  ☆55Updated 4 years ago
• thegregyang / NTK4A
  Code for the paper: "Tensor Programs II: Neural Tangent Kernel for Any Architecture"
  ☆105Updated 4 years ago