Alternatives and similar repositories for Gaussian-Process:

Users that are interested in Gaussian-Process are comparing it to the libraries listed below

• WayneDW / Contour-Stochastic-Gradient-Langevin-Dynamics
  An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)
  ☆40Updated 2 years ago
• OxfordML / bayesquad
  Library for Bayesian Quadrature
  ☆31Updated 5 years ago
• facebookresearch / alebo
  Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization
  ☆41Updated 3 years ago
• IdahoLabResearch / BIhNNs
  The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural …
  ☆14Updated 2 years ago
• juliusberner / deep_kolmogorov
  Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (NeurIPS 2020)
  ☆22Updated 2 years ago
• misokg / NIPS2017
  Multi-Information Source Optimization
  ☆22Updated 5 years ago
• zhulingchen / tfp-tutorial
  TensorFlow Probability Tutorial
  ☆37Updated 5 years ago
• facebookresearch / bo_pr
  Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization
  ☆72Updated 2 years ago
• samuelstanton / conformal-bayesopt
  Bayesian optimization with conformal coverage guarantees
  ☆27Updated 2 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆31Updated 3 years ago
• nikita-0209 / mf-al-gfn
  Multi-Fidelity Active Learning with GFlowNets
  ☆7Updated 8 months ago
• Ryan-Rhys / Heteroscedastic-BO
  Heteroscedastic Bayesian Optimisation in Numpy
  ☆21Updated 2 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆44Updated 5 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
• Isaac-Somerville / Neural-Networks-for-Solving-Differential-Equations
  Codebase for Master's dissertation in Mathematics at Durham University. Topic: applying neural networks to differential equations. Grade:…
  ☆11Updated last year
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 2 years ago
• jorgemarpa / PELS-VAE
  Physics-Enhanced Latent Space Variational Autoencoder
  ☆8Updated 2 years ago
• gpschool / gpss21
  ☆12Updated 2 years ago
• jpzxshi / sympnets
  ☆27Updated 3 years ago
• j-wilson / MaximizingAcquisitionFunctions
  Code for "Maximizing Acquisition Functions for Bayesian Optimization"
  ☆13Updated 6 years ago
• PhIMaL / temporal_normalizing_flows
  ☆11Updated 3 years ago
• ORF522 / companion
  Supporting material for Princeton ORF522
  ☆12Updated 3 months ago
• gerdm / bayes
  Neat Bayesian machine learning examples
  ☆55Updated 2 months ago
• abdulfatir / sampling-methods-numpy
  This repository contains implementations of some basic sampling methods in numpy.
  ☆66Updated 5 years ago
• facebookresearch / robust_mobo
  Code for "Robust Multi-Objective Bayesian Optimization Under Input Noise"
  ☆54Updated 2 years ago
• mfinzi / constrained-hamiltonian-neural-networks
  ☆105Updated 3 years ago
• theevann / dl4sci-pytorch-webinar
  ☆55Updated 4 years ago
• datasailors / bayesian_calibration
  Bayesian calibration using Tensorflow Probability
  ☆34Updated 6 years ago
• ghliu / snopt
  Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight
  ☆52Updated 3 years ago
• distillpub / post--bayesian-optimization
  Exploring Bayesian Optimization
  ☆74Updated 3 years ago