Alternatives and similar repositories for convnets-as-gps

Users that are interested in convnets-as-gps are comparing it to the libraries listed below

• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆65Updated 4 years ago
• AMLab-Amsterdam / SEVDL_MGP
  Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…
  ☆30Updated 4 years ago
• pomonam / NoisyNaturalGradient
  TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
  ☆60Updated 6 years ago
• joelouismarino / iterative_inference
  Implementation of iterative inference in deep latent variable models
  ☆43Updated 5 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 5 years ago
• da-molchanov / variance-networks
  Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019
  ☆39Updated 5 years ago
• YingzhenLi / Dropout_BBalpha
  Implementations of the ICML 2017 paper (with Yarin Gal)
  ☆38Updated 7 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• emtiyaz / vmp-for-svae
  Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)
  ☆44Updated 7 years ago
• bioinf-jku / coulomb_gan
  Implementation of Coulomb GANs
  ☆62Updated 3 years ago
• pawni / BayesByHypernet
  Code for the paper Implicit Weight Uncertainty in Neural Networks
  ☆65Updated 5 years ago
• CW-Huang / torchkit
  ☆37Updated 5 years ago
• cjratcliff / variational-dropout
  TensorFlow implementation of the method from Variational Dropout Sparsifies Deep Neural Networks, Molchanov et al. (2017)
  ☆16Updated 8 years ago
• renmengye / meta-optim-public
  Understanding Short-Horizon Bias in Stochastic Meta-Optimization
  ☆37Updated 7 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• wlwkgus / NoisyNaturalGradient
  Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference"
  ☆121Updated 6 years ago
• IraKorshunova / bruno
  a deep recurrent model for exchangeable data
  ☆34Updated 4 years ago
• insperatum / vhe
  The Variational Homoencoder: Learning to learn high capacity generative models from few examples
  ☆34Updated last year
• cmaddis / astar-sampling
  A generic Monte Carlo method based on the Gumbel-Max trick.
  ☆32Updated 9 years ago
• Orcuslc / OrthNet
  TensorFlow, PyTorch and Numpy layers for generating Orthogonal Polynomials
  ☆31Updated 7 years ago
• y0ast / VIMCO
  Implementation of "Variational Inference for Monte Carlo Objectives"
  ☆21Updated 4 years ago
• rdevon / BGAN
  boundary-seeking generative adversarial networks
  ☆46Updated 7 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆63Updated 7 years ago
• dilinwang820 / adaptive-f-divergence
  A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"
  ☆21Updated 6 years ago
• kefirski / variational_dropout
  Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch
  ☆49Updated 7 years ago
• artix41 / AVO-pytorch
  Implementation of Adversarial Variational Optimization in PyTorch
  ☆43Updated 6 years ago
• DartML / SteinGAN
  code for steinGAN - Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning
  ☆27Updated 6 years ago
• thjashin / spectral-stein-grad
  Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)
  ☆33Updated 2 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 8 years ago
• lxuechen / inference-suboptimality
  Code for "Inference Suboptimality in Variational Autoencoders"
  ☆14Updated 5 years ago