Alternatives and similar repositories for gpss21

Users that are interested in gpss21 are comparing it to the libraries listed below

• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 2 years ago
• vr308 / Generalised-Gaussian-Processes
  Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods
  ☆22Updated last year
• jejjohnson / uncertain_gps
  Exploring how to to deal with uncertain inputs with gaussian process regression models.
  ☆27Updated 4 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆72Updated 4 years ago
• OxfordML / bayesquad
  Library for Bayesian Quadrature
  ☆32Updated 6 years ago
• lbl-camera / fvGP
  A software package for flexible HPC GPs
  ☆16Updated this week
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆24Updated 2 years ago
• MJHutchinson / ExtrinsicGaugeIndependentVectorGPs
  A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes
  ☆25Updated 3 years ago
• mingdeyu / DGP
  Python package 'dgpsi' for deep and linked Gaussian process emulations
  ☆27Updated 4 months ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆29Updated 2 years ago
• aidanscannell / GPJax
  Minimal Gaussian process library in JAX with a simple (custom) approach to state management.
  ☆12Updated last year
• AaltoML / spatio-temporal-GPs
  Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'
  ☆47Updated 3 years ago
• ulissigroup / uncertainty_benchmarking
  Various code/notebooks to benchmark different ways we could estimate uncertainty in ML predictions.
  ☆41Updated 3 years ago
• samuelstanton / conformal-bayesopt
  Bayesian optimization with conformal coverage guarantees
  ☆28Updated 2 years ago
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 4 years ago
• Ryan-Rhys / Heteroscedastic-BO
  Heteroscedastic Bayesian Optimisation in Numpy
  ☆21Updated 2 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆42Updated 10 months ago
• PrincetonLIPS / AHGP
  [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)
  ☆21Updated 4 years ago
• PhIMaL / temporal_normalizing_flows
  ☆11Updated 4 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆19Updated 3 years ago
• misokg / NIPS2017
  Multi-Information Source Optimization
  ☆23Updated 6 years ago
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆51Updated last year
• secondmind-labs / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆11Updated 2 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• jejjohnson / gp_model_zoo
  Literature and light wrappers for gaussian process models.
  ☆46Updated 3 years ago
• fidero / gp-derivative
  Example code to speed up GP inference with gradients for high-dimensional inputs.
  ☆14Updated 3 years ago
• facebookresearch / alebo
  Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization
  ☆41Updated 3 years ago
• briandesilva / discovery-of-physics-from-data
  Code to accompany the paper "Discovery of Physics from Data: Universal Laws and Discrepancies"
  ☆27Updated 4 years ago
• LiuHaiTao01 / SVSHGP
  Stochastic variational heteroscedastic Gaussian process
  ☆15Updated 6 years ago
• vr308 / GPLVM
  Implementation of GPLVM and Bayesian GPLVM in pytorch/gpytorch
  ☆15Updated 3 years ago