Alternatives and similar repositories for epig

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

• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆90Updated 5 years ago
• VectorInstitute / vbll
  Simple (and cheap!) neural network uncertainty estimation
  ☆78Updated 2 months ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆43Updated 6 months ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆58Updated 4 years ago
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆65Updated last year
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 3 years ago
• activatedgeek / svgd
  PyTorch implementation of Stein Variational Gradient Descent
  ☆47Updated 2 years ago
• TyXe-BDL / TyXe
  ☆155Updated 3 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 6 years ago
• dngfra / repulsive_ensembles
  Repo for our paper "Repulsive deep ensembles are Bayesian"
  ☆19Updated 4 years ago
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆25Updated 3 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• aleximmer / BNN-predictions
  Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021
  ☆16Updated 2 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆21Updated 3 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆112Updated 4 years ago
• MachineLearningLifeScience / stochman
  Algorithms for computations on random manifolds made easier
  ☆94Updated 2 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆74Updated 5 years ago
• ludwigwinkler / pytorch_MCMC
  Lightweight MCMC sampling for PyTorch Models aka My Corona Project
  ☆51Updated 4 months ago
• cambridge-mlg / DUN
  Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
  ☆78Updated 2 years ago
• izmailovpavel / understandingbdl
  ☆251Updated 3 years ago
• tranbahien / you-need-a-good-prior
  All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)
  ☆20Updated 3 years ago
• automl / TransformersCanDoBayesianInference
  Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
  ☆244Updated last year
• cyz-ai / neural-approx-ss-lfi
  Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models
  ☆20Updated 3 years ago
• treforevans / uci_datasets
  Regression datasets from the UCI repository with standardized test-train splits.
  ☆51Updated 3 years ago
• ae-foster / dad
  Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
  ☆39Updated 4 years ago
• YannDubs / Neural-Process-Family
  Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
  ☆227Updated last year
• bmucsanyi / untangle
  Large-scale uncertainty benchmark in deep learning.
  ☆64Updated 7 months ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆78Updated 4 years ago
• microsoft / bayesianize
  Bayesianize: A Bayesian neural network wrapper in pytorch
  ☆90Updated last year
• tung-nd / TNP-pytorch
  Official implementation of Transformer Neural Processes
  ☆78Updated 3 years ago