Alternatives and similar repositories for TensorBNN:

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

• eth-cscs / abcpy-models
  ☆12Updated 3 years ago
• deepskies / DeeplyUncertain-Public
  ☆28Updated 2 years ago
• flatironinstitute / bayes-kit
  Bayesian inference and posterior analysis for Python
  ☆44Updated last year
• vr308 / Generalised-Gaussian-Processes
  Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods
  ☆22Updated last year
• EEA-sensors / parallel-gps
  GPFlow based implementation of temporal parallellization of state space GPs
  ☆15Updated 2 years ago
• justindomke / pangolin
  probabilistic programming focused on fun
  ☆40Updated 5 months ago
• bob-carpenter / adaptive-hmc
  Self-tuning HMC algorithms and evaluations
  ☆18Updated 5 months ago
• danhphan / workshops
  workshops
  ☆12Updated 2 years ago
• gabriuma / basis_functions_approach_to_GP
  ☆54Updated 2 years ago
• lee-group-cmu / DeepCDE
  Neural networks for conditional density estimation
  ☆12Updated 4 years ago
• mloning / sktime-m4
  Using sktime to replicate and extend the M4 forecasting competition
  ☆16Updated 4 years ago
• abhiagwl / vistan
  A simple library to run variational inference on Stan models.
  ☆30Updated last year
• 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
  ☆63Updated 2 months ago
• sbi-dev / pyknos
  Conditional density estimation with neural networks
  ☆30Updated 2 months ago
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 4 years ago
• jhuggins / viabel
  Efficient, lightweight variational inference and approximation bounds
  ☆43Updated last year
• pierrejacob / unbiasedmcmc
  Unbiased Markov chain Monte Carlo with couplings
  ☆29Updated 2 years ago
• StannisZhou / mixed_hmc
  ☆12Updated 3 years ago
• compops / pmh-tutorial
  Source code and data for the tutorial: "Getting started with particle Metropolis-Hastings for inference in nonlinear models"
  ☆28Updated 6 years ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆30Updated 8 months ago
• chris-nemeth / sgmcmc-review-paper
  The code in this repository follows the paper "Stochastic gradient MCMC"
  ☆26Updated 5 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆41Updated 8 months ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆124Updated 5 months ago
• AdrienCorenflos / particle_mala
  Gradient-informed particle MCMC methods
  ☆11Updated last year
• gerdm / bayes
  Neat Bayesian machine learning examples
  ☆55Updated 2 months ago
• martiningram / mcmc_runtime_comparison
  Compares Stan, PyMC, and PyMC + JAX numpyro sampler on a model for tennis
  ☆32Updated 2 years ago
• betanalpha / quarto_chapters
  Book Chapter Drafts
  ☆29Updated 6 months ago
• wesselb / mlkernels
  Kernels, the machine learning ones
  ☆14Updated 2 years ago
• pnkraemer / tornadox
  Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…
  ☆21Updated 8 months ago