Alternatives and similar repositories for GPt:

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

• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆109Updated 3 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆69Updated 4 years ago
• aboustati / dgplib
  Library for Deep Gaussian Processes based on GPflow
  ☆19Updated 4 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆81Updated 4 years ago
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆23Updated 2 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆53Updated 11 months ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆17Updated 3 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 5 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆64Updated 5 years ago
• thjashin / solvegp
  Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)
  ☆22Updated 3 years ago
• oxcsml / ML_bazaar
  OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.
  ☆93Updated 3 years ago
• hegdepashupati / differential-dgp
  Implementation of stochastic variational inference for differentially deep gaussian processes
  ☆15Updated 6 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆148Updated 5 years ago
• aterenin / SparseGaussianProcesses.jl
  A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.
  ☆33Updated 4 years ago
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆32Updated last year
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆41Updated 6 months ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 2 years ago
• cambridge-mlg / sghmc_dgp
  ☆28Updated 6 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 5 years ago
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆23Updated 9 years ago
• JTT94 / filterflow
  Extensible Tensorflow library for differentiable particle filtering. ICML 2021.
  ☆40Updated 2 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆81Updated 7 months ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆29Updated 7 months ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆88Updated 4 years ago
• wesselb / NeuralProcesses.jl
  A framework for composing Neural Processes in Julia
  ☆76Updated 3 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 6 years ago
• karlnapf / kernel_exp_family
  Various estimators of the infinite dimensional exponential family model
  ☆15Updated 7 years ago