Alternatives and similar repositories for kbfgs_neurips2020_public

Users that are interested in kbfgs_neurips2020_public are comparing it to the libraries listed below

• fmeirinhos / pytorch-hessianfree
  PyTorch implementation of Hessian Free optimisation
  ☆43Updated 5 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆52Updated 4 years ago
• deep-lab / DeepnetHessian
  Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians (ICML 2019)
  ☆17Updated 6 years ago
• cybertronai / pytorch-sso
  PyTorch-SSO: Scalable Second-Order methods in PyTorch
  ☆146Updated last year
• google / spectral-density
  Hessian spectral density estimation in TF and Jax
  ☆123Updated 4 years ago
• alecwangcq / KFAC-Pytorch
  Pytorch implementation of KFAC and E-KFAC (Natural Gradient).
  ☆132Updated 5 years ago
• bobby-he / Neural_Tangent_Kernel
  ☆67Updated 6 years ago
• thegregyang / NTK4A
  Code for the paper: "Tensor Programs II: Neural Tangent Kernel for Any Architecture"
  ☆107Updated 4 years ago
• gaoliyao / Replica_Exchange_Stochastic_Gradient_MCMC
  Code for Non-convex Learning via Replica Exchange Stochastic Gradient MCMC, ICML 2020.
  ☆25Updated 4 years ago
• f-dangel / hbp
  Hessian backpropagation (HBP): PyTorch extension of backpropagation for block-diagonal curvature matrix approximations
  ☆20Updated 2 years ago
• tudor-berariu / fisher-information-matrix
  PyTorch implementation of FIM and empirical FIM
  ☆61Updated 6 years ago
• AnonymousNIPS2019 / DeepnetHessian
  The Full Spectrum of Deepnet Hessians at Scale: Dynamics with SGD Training and Sample Size
  ☆17Updated 6 years ago
• fwcore / mean-field-theory-deep-learning
  paper lists and information on mean-field theory of deep learning
  ☆76Updated 6 years ago
• JunLi-Galios / Optimization-on-Stiefel-Manifold-via-Cayley-Transform
  Efficient Riemannian Optimization on Stiefel Manifold via Cayley Transform
  ☆40Updated 6 years ago
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆47Updated 3 months ago
• cemanil / LNets
  Lipschitz Neural Networks described in "Sorting Out Lipschitz Function Approximation" (ICML 2019).
  ☆56Updated 5 years ago
• avirmaux / lipEstimation
  ☆58Updated 2 years ago
• team-approx-bayes / fromp
  Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"
  ☆44Updated 4 years ago
• AlexanderMath / fasth
  Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.
  ☆75Updated 10 months ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆58Updated 3 years ago
• mariogeiger / feature_lazy
  ☆14Updated 3 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• gd-zhang / Weight-Decay
  Regularization, Neural Network Training Dynamics
  ☆14Updated 5 years ago
• JonasGeiping / fullbatchtraining
  Training vision models with full-batch gradient descent and regularization
  ☆37Updated 2 years ago
• leiwu0 / sgd.stability
  Analyze the dynamic stability of SGD
  ☆12Updated 6 years ago
• toshas / sttp
  Spectral Tensor Train Parameterization of Deep Learning Layers
  ☆15Updated 3 years ago
• cybertronai / autograd-hacks
  ☆157Updated 2 years ago
• ssagawa / overparam_spur_corr
  An Investigation of Why Overparameterization Exacerbates Spurious Correlations
  ☆31Updated 4 years ago
• rgrosse / csc2541_examples
  ☆29Updated 4 years ago