Alternatives and similar repositories for stein_thinning

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

• secondmind-labs / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆12Updated 2 years ago
• frgsimpson / kitt
  Kernel Identification Through Transformers
  ☆14Updated 2 years ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆32Updated last year
• LaurenceA / bayesfunc
  ☆15Updated 3 years ago
• runame / laplace-refinement
  Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
  ☆10Updated 3 years ago
• pmorenoz / ModularGP
  Modular Gaussian Processes
  ☆16Updated 4 years ago
• joneswack / dp-rfs
  This repository contains PyTorch implementations of various random feature maps for dot product kernels.
  ☆22Updated last year
• Sulam-Group / k-rcps
  "How to Trust Your Diffusion Models: A Convex Optimization Approach to Conformal Risk Control"
  ☆18Updated this week
• PrincetonLIPS / AHGP
  [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)
  ☆23Updated 5 years ago
• fidero / gp-derivative
  Example code to speed up GP inference with gradients for high-dimensional inputs.
  ☆14Updated 4 years ago
• NickHunt-Smith / MCMC-diffusion
  A Metropolis-Hastings MCMC sampler accelerated via diffusion models
  ☆16Updated last year
• MLO-lab / Uncertainty_Estimates_via_BVD
  The official source code to: Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition (AISTATS'23)
  ☆11Updated 2 years ago
• desResLab / LINFA
  A Python library for variational inference with normalizing flow and annealing
  ☆15Updated 9 months ago
• AdrienCorenflos / particle_mala
  Gradient-informed particle MCMC methods
  ☆12Updated last year
• fredhallgren / nystrompca
  Efficient non-linear PCA through kernel PCA with the Nyström method
  ☆13Updated 2 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
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆43Updated last year
• AaltoML / spatio-temporal-GPs
  Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'
  ☆47Updated 4 years ago
• kimvc7 / HDL
  ☆12Updated 2 years ago
• HanbaekLyu / NNetwork
  Custom graph/network/multi-weighted network class based on storing list of neighbors for each nodes (as opposed to edge list) for scalabl…
  ☆12Updated last year
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆74Updated 5 years ago
• topipa / gp-varsel-kl-var
  ☆14Updated 6 years ago
• plugyawn / gp-zoo
  A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably incl…
  ☆14Updated 3 years ago
• aleximmer / BNN-predictions
  Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021
  ☆16Updated 3 years ago
• cambridge-mlg / sgd-gp
  Public code for running Stochastic Gradient Descent on GPs.
  ☆39Updated 8 months ago
• federicobergamin / riemannian-laplace-approximation
  Repository for the paper "Riemannian Laplace approximations for Bayesian neural networks"
  ☆11Updated 2 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆34Updated 3 years ago
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆25Updated 3 years ago
• tijana-zrnic / active-inference
  ☆18Updated last year
• modichirag / GSM-VI
  Code for Gaussian Score Matching Variational Inference
  ☆35Updated 10 months ago