Alternatives and similar repositories for pyro:

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

• gatsby-sahani / gp-sde
  ☆14Updated last year
• ae-foster / dad
  Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
  ☆30Updated 3 years ago
• fbickfordsmith / epig
  Bayesian active learning with EPIG data acquisition
  ☆28Updated last month
• LaurenceA / bayesfunc
  ☆15Updated 2 years ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆53Updated last year
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 5 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆52Updated 4 years ago
• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆24Updated 5 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆70Updated 4 years ago
• ntienvu / KnownOptimum_BO
  Release code for ICML2020 Knowing The What But Not The Where in Bayesian Optimization
  ☆15Updated 2 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆27Updated last year
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 2 years ago
• Jiacheng-Zhu-AIML / WGPOT
  The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
  ☆52Updated 4 years ago
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆86Updated 3 years ago
• AaltoML / scalable-inference-in-sdes
  Methods and experiments for assumed density SDE approximations
  ☆11Updated 3 years ago
• yorkerlin / VB-MixEF
  Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"
  ☆18Updated 4 years ago
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• cagatayyildiz / npode
  Learning unknown ODE models with Gaussian processes
  ☆26Updated 6 years ago
• MatthieuDarcy / KernelFlows
  ☆12Updated 2 years ago
• dtak / ocbnn-public
  General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
  ☆38Updated 2 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆19Updated 3 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• ludwigwinkler / pytorch_MCMC
  Lightweight MCMC sampling for PyTorch Models aka My Corona Project
  ☆45Updated 4 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 2 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆62Updated 2 months ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• zi-w / Max-value-Entropy-Search
  Max-value Entropy Search for Efficient Bayesian Optimization
  ☆71Updated 3 years ago
• ltiao / bore
  Bayesian Optimization with Density-Ratio Estimation
  ☆23Updated 2 years ago
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆48Updated 4 years ago