Alternatives and similar repositories for neuralprocesses

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

• YannDubs / Neural-Process-Family
  Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
  ☆223Updated last year
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆24Updated 2 years ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆127Updated 9 months ago
• jejjohnson / gp_model_zoo
  Literature and light wrappers for gaussian process models.
  ☆48Updated 4 years ago
• cambridge-mlg / convcnp
  Implementation of the Convolutional Conditional Neural Process
  ☆124Updated 4 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆43Updated last year
• TyXe-BDL / TyXe
  ☆151Updated 2 years ago
• probabilists / lampe
  Likelihood-free AMortized Posterior Estimation with PyTorch
  ☆130Updated 11 months ago
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆104Updated last year
• GaussianProcessesCambridge / meetup-resources
  Collection of resources from each meetup event
  ☆13Updated 4 years ago
• AaltoML / spatio-temporal-GPs
  Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'
  ☆47Updated 3 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 2 years ago
• anh-tong / signax
  Signax: Signature computation in JAX
  ☆31Updated 6 months ago
• mingdeyu / DGP
  Python package 'dgpsi' for deep and linked Gaussian process emulations
  ☆27Updated this week
• schmidtjonathan / Climate2Weather
  This code accompanies the manuscript "A Generative Framework for Probabilistic, Spatiotemporally Coherent Downscaling of Climate Simulati…
  ☆23Updated 2 weeks ago
• wesselb / stheno
  Gaussian process modelling in Python
  ☆223Updated 7 months ago
• AaltoML / BayesNewton
  Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
  ☆234Updated last year
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆171Updated 3 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆72Updated 4 years ago
• jejjohnson / uncertain_gps
  Exploring how to to deal with uncertain inputs with gaussian process regression models.
  ☆27Updated 4 years ago
• DanieleGammelli / pyro-torch-normalizing-flows
  Implementations of Normalizing Flows in Pytorch/Pyro
  ☆19Updated 5 years ago
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆47Updated 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
• jfcrenshaw / pzflow
  Probabilistic modeling of tabular data with normalizing flows.
  ☆57Updated last month
• Information-Fusion-Lab-Umass / NuX
  Normalizing Flows using JAX
  ☆84Updated last year
• sbi-benchmark / sbibm
  Simulation-based inference benchmark
  ☆100Updated 6 months ago
• cornellius-gp / linear_operator
  A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch
  ☆112Updated 4 months ago
• evwalz / easyuq
  ☆11Updated last year
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆67Updated 6 months ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆73Updated 3 years ago