Alternatives and similar repositories for noisy-K-FAC:

Users that are interested in noisy-K-FAC are comparing it to the libraries listed below

• pomonam / NoisyNaturalGradient
  TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
  ☆60Updated 6 years ago
• thjashin / spectral-stein-grad
  Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)
  ☆32Updated last year
• plai-group / tvo
  Code for the Thermodynamic Variational Objective
  ☆26Updated 2 years ago
• ermongroup / higher_order_invariance
  Code for "Accelerating Natural Gradient with Higher-Order Invariance"
  ☆30Updated 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
  ☆46Updated 4 years ago
• CW-Huang / torchkit
  ☆37Updated 5 years ago
• gd-zhang / Weight-Decay
  Regularization, Neural Network Training Dynamics
  ☆14Updated 5 years ago
• YingzhenLi / SteinGrad
  Code release for the ICLR paper
  ☆20Updated 6 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• dilinwang820 / adaptive-f-divergence
  A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"
  ☆20Updated 6 years ago
• franrruiz / vcd_divergence
  Code to minimize the Variational Contrastive Divergence (VCD)
  ☆28Updated 5 years ago
• mingzhang-yin / SIVI
  A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…
  ☆53Updated 3 months ago
• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆65Updated 4 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆51Updated 4 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 3 years ago
• jiamings / ais
  Annealed Importance Sampling (AIS) for generative models.
  ☆16Updated 6 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 4 years ago
• wellecks / vaes
  Variational Autoencoders & Normalizing Flows Project
  ☆19Updated 8 years ago
• lxuechen / inference-suboptimality
  Code for "Inference Suboptimality in Variational Autoencoders"
  ☆14Updated 4 years ago
• widedeepnetworks / widedeepnetworks
  Code for the paper Gaussian process behaviour in wide deep networks
  ☆48Updated 6 years ago
• modestyachts / neural_kernels_code
  ☆36Updated 3 years ago
• ermongroup / f-EBM
  Code for "Training Deep Energy-Based Models with f-Divergence Minimization" ICML 2020
  ☆36Updated last year
• AMLab-Amsterdam / SEVDL_MGP
  Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…
  ☆31Updated 4 years ago
• ermongroup / lagvae
  Lagrangian VAE
  ☆28Updated 6 years ago
• joelouismarino / iterative_inference
  Implementation of iterative inference in deep latent variable models
  ☆43Updated 5 years ago
• Runjing-Liu120 / RaoBlackwellizedSGD
  A public repository for our paper, Rao-Blackwellized Stochastic Gradients for Discrete Distributions
  ☆22Updated 5 years ago
• YingzhenLi / vae_renyi_divergence
  A tensorflow implementation of VAE training with Renyi divergence
  ☆31Updated 8 years ago
• AVMCMC / AuxiliaryVariationalMCMC
  Code required to reproduce the experiments in Auxiliary Variational MCMC
  ☆17Updated 6 years ago