Alternatives and similar repositories for Helmholtz-GP

Users that are interested in Helmholtz-GP are comparing it to the libraries listed below

• wesselb / neuralprocesses
  A framework for composing Neural Processes in Python
  ☆88Updated 10 months ago
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆24Updated 2 years ago
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆63Updated last year
• tranbahien / you-need-a-good-prior
  All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)
  ☆20Updated 3 years ago
• YannDubs / Neural-Process-Family
  Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
  ☆226Updated last year
• probabilists / lampe
  Likelihood-free AMortized Posterior Estimation with PyTorch
  ☆131Updated last year
• huangdaolang / robust-sbi
  Learning Robust Statistics for Simulation-Based Inference Under Model Misspecification (Huang et al., Neurips 2023)
  ☆11Updated 4 months ago
• ludwigwinkler / pytorch_MCMC
  Lightweight MCMC sampling for PyTorch Models aka My Corona Project
  ☆51Updated 3 months ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆21Updated 3 years ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆127Updated last year
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆47Updated 3 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆43Updated last year
• alan-turing-institute / mogp-emulator
  Package for fitting Gaussian Process Emulators to multiple output computer simulation results.
  ☆52Updated 2 years ago
• mingdeyu / DGP
  Python package 'dgpsi' for deep and linked Gaussian process emulations
  ☆27Updated 3 weeks ago
• francois-rozet / sda
  Official implementation of Score-based Data Assimilation
  ☆73Updated last year
• cambridge-mlg / convcnp
  Implementation of the Convolutional Conditional Neural Process
  ☆127Updated 4 years ago
• jejjohnson / gp_model_zoo
  Literature and light wrappers for gaussian process models.
  ☆47Updated 4 years ago
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆105Updated 2 years ago
• ae-foster / dad
  Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
  ☆37Updated 4 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 3 years ago
• sbi-benchmark / sbibm
  Simulation-based inference benchmark
  ☆105Updated 9 months ago
• mackelab / simformer
  Combination of transformers and diffusion models for flexible all-in-one simulation-based inference
  ☆74Updated 4 months ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆73Updated 5 years ago
• danielward27 / flowjax
  ☆198Updated 2 weeks ago
• schmidtjonathan / Climate2Weather
  This code accompanies the manuscript "A Generative Framework for Probabilistic, Spatiotemporally Coherent Downscaling of Climate Simulati…
  ☆30Updated 3 months ago
• pnkraemer / matfree
  Matrix-free linear algebra in JAX.
  ☆148Updated last week
• konstantinos-p / Bayesian-Neural-Networks-Reading-List
  A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesi…
  ☆58Updated 2 years ago
• PrincetonLIPS / AHGP
  [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)
  ☆23Updated 4 years ago
• team-approx-bayes / ivon
  IVON optimizer for neural networks based on variational learning.
  ☆72Updated last year
• modichirag / GSM-VI
  Code for Gaussian Score Matching Variational Inference
  ☆35Updated 8 months ago