Alternatives and similar repositories for logistic-reg-bbvi-blog:

Users that are interested in logistic-reg-bbvi-blog are comparing it to the libraries listed below

• mingzhang-yin / SIVI
  A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…
  ☆53Updated 5 months ago
• blei-lab / ars-reparameterization
  Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)
  ☆39Updated 7 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 5 years ago
• YingzhenLi / vae_renyi_divergence
  A tensorflow implementation of VAE training with Renyi divergence
  ☆31Updated 8 years ago
• YingzhenLi / VRbound
  code release for the NIPS 2016 paper
  ☆26Updated 8 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated 9 months ago
• daeilkim / bbvi
  Black Box Variational Inference
  ☆14Updated 9 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 5 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆82Updated 4 years ago
• namkoong-lab / robustopt
  ☆42Updated 6 years ago
• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆65Updated 4 years ago
• rachtsingh / ibp_vae
  mean-field and structured VAEs for the IBP
  ☆23Updated 7 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆63Updated 6 years ago
• markvdw / GPflow-inter-domain
  Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables
  ☆13Updated 7 years ago
• widedeepnetworks / widedeepnetworks
  Code for the paper Gaussian process behaviour in wide deep networks
  ☆47Updated 6 years ago
• aburnap / Mixed-Membership-Stochastic-Blockmodel
  Mixed Membership Stochastic Blockmodel Implementation with 3 Inference Schemes
  ☆24Updated 9 years ago
• franrruiz / augment-reduce
  Code for Augment & Reduce, a scalable stochastic algorithm for large categorical distributions
  ☆10Updated 6 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• ron-amit / meta-learning-adjusting-priors
  Implementation of the paper "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory", Ron Amit and Ron Meir, ICML 2018
  ☆22Updated 5 years ago
• xiaoshuai09 / Wasserstein-Learning-For-Point-Process
  learning point processes by means of optimal transport and wasserstein distance
  ☆54Updated 7 years ago
• criteo-research / optimization-continuous-action-crm
  ☆30Updated 4 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆27Updated last year
• pawni / BayesByHypernet
  Code for the paper Implicit Weight Uncertainty in Neural Networks
  ☆65Updated 5 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• otokonoko8 / implicit-variational-inference
  The collection of recent papers about variational inference
  ☆85Updated 5 years ago
• PGM-Lab / PAC2BAYES
  This repository contains the Python code to reproduce all the figures and experiments presented in the paper: Masegosa, Andrés. R., Learn…
  ☆9Updated 2 years ago
• oxcsml / kerpy
  python code for kernel methods
  ☆38Updated 6 years ago
• hichamjanati / srf
  Random Fourier Features
  ☆50Updated 7 years ago
• jamesmcinerney / vbmm
  Variational inference for Gaussian mixture models
  ☆35Updated 11 years ago