Alternatives and similar repositories for gaussianprocesses:

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

• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• LaurenceA / bayesfunc
  ☆15Updated 2 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆27Updated 3 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆55Updated 3 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 5 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆81Updated 7 months ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆70Updated 2 years ago
• MichaelArbel / GeneralizedEBM
  ☆53Updated 5 months ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 4 years ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆41Updated last year
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆88Updated 4 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆80Updated 4 years ago
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆43Updated 4 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆30Updated 3 years ago
• ratschlab / repulsive_ensembles
  Repo for our paper "Repulsive deep ensembles are Bayesian"
  ☆19Updated 3 years ago
• dimkal89 / rvae
  ☆37Updated 4 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆17Updated 3 years ago
• changliu00 / AWGF
  Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)
  ☆22Updated 5 years ago
• thu-ml / fpovi
  Code for "Function Space Particle Optimization for Bayesian Neural Networks"
  ☆17Updated 2 years ago
• xinshi-chen / ParticleFlowBayesRule
  Pytorch implementation for "Particle Flow Bayes' Rule"
  ☆13Updated 5 years ago
• hichamjanati / spatio-temporal-alignements
  Spatio-temporal alignements: Optimal transport in space and time
  ☆43Updated 3 years ago
• cambridge-mlg / cnn-gp
  Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…
  ☆32Updated 4 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 3 years ago
• tranbahien / you-need-a-good-prior
  All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)
  ☆21Updated 2 years ago
• JonathanWenger / pycalib
  Non-Parametric Calibration for Classification (AISTATS 2020)
  ☆19Updated 2 years ago
• activatedgeek / svgd
  PyTorch implementation of Stein Variational Gradient Descent
  ☆41Updated last year
• AVMCMC / AuxiliaryVariationalMCMC
  Code required to reproduce the experiments in Auxiliary Variational MCMC
  ☆17Updated 6 years ago
• fbickfordsmith / epig
  Bayesian active learning with EPIG data acquisition
  ☆26Updated 2 weeks ago
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆23Updated 2 years ago
• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆24Updated 5 years ago