Alternatives and similar repositories for hybrid-inference

Users that are interested in hybrid-inference 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…
  ☆54Updated 10 months ago
• HeddaCohenIndelman / Learning-Gumbel-Sinkhorn-Permutations-w-Pytorch
  LEARNING LATENT PERMUTATIONS WITH GUMBEL-SINKHORN NETWORKS IMPLEMENTATION WITH PYTORCH
  ☆79Updated 2 years ago
• ermongroup / subsets
  Code for Reparameterizable Subset Sampling via Continuous Relaxations, IJCAI 2019.
  ☆57Updated last year
• SaynaEbrahimi / UCB
  Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020
  ☆75Updated 4 years ago
• zzhang1987 / Factor-Graph-Neural-Network
  Factor Graph Neural Network
  ☆74Updated 4 years ago
• xqding / Importance_Weighted_Autoencoders
  A PyTorch Implementation of the Importance Weighted Autoencoders
  ☆39Updated 6 years ago
• oskopek / mvae
  Mixed-curvature Variational Autoencoders (ICLR 2020)
  ☆65Updated 4 years ago
• alexalemi / vib_demo
  ☆91Updated 3 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• uber-research / vargp
  Variational Auto-Regressive Gaussian Processes for Continual Learning
  ☆21Updated 4 years ago
• CUAI / Differentiable-Frechet-Mean
  [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
  ☆56Updated 3 years ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆77Updated 4 years ago
• chingyaoc / kV-Margin
  NeurIPS 2021, Code for Measuring Generalization with Optimal Transport
  ☆28Updated 3 years ago
• mingzhang-yin / ARM-gradient
  Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)
  ☆28Updated 6 years ago
• Jiacheng-Zhu-AIML / WGPOT
  The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
  ☆53Updated 5 years ago
• FerranAlet / modular-metalearning
  ☆78Updated 4 years ago
• francoispierrepaty / SubspaceRobustWasserstein
  Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"
  ☆29Updated 6 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• microsoft / conservative-uncertainty-estimation-random-priors
  Source code for paper Conservative Uncertainty Estimation By Fitting Prior Networks (ICLR 2020)
  ☆21Updated 2 years ago
• singhgautam / snp
  This is the official source code for Sequential Neural Processes.
  ☆40Updated 2 years ago
• sharpenb / Posterior-Network
  Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)
  ☆78Updated 3 years ago
• fpcasale / GPPVAE
  Gaussian Process Prior Variational Autoencoder
  ☆84Updated 6 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• tuananhle7 / aesmc
  Library for Auto-Encoding Sequential Monte Carlo
  ☆18Updated last year
• cunningham-lab / igr
  ☆30Updated 4 years ago
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆27Updated 5 years ago
• thu-ml / fpovi
  Code for "Function Space Particle Optimization for Bayesian Neural Networks"
  ☆18Updated 2 years ago
• jsikyoon / bmaml
  This repository contains implementations of the paper, Bayesian Model-Agnostic Meta-Learning.
  ☆60Updated 6 years ago
• tvayer / SGW
  Code for Sliced Gromov-Wasserstein
  ☆69Updated 5 years ago
• otokonoko8 / deep-Bayesian-nonparametrics-papers
  The collection of papers about combining deep learning and Bayesian nonparametrics
  ☆121Updated 5 years ago