Alternatives and similar repositories for BLNNbook

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

• GAMES-UChile / mogptk
  Multi-Output Gaussian Process Toolkit
  ☆175Updated last month
• TyXe-BDL / TyXe
  ☆152Updated 2 years ago
• probabilisticai / probai-2022
  Materials of the Nordic Probabilistic AI School 2022.
  ☆181Updated 2 years ago
• probabilisticai / probai-2023
  Materials of the Nordic Probabilistic AI School 2023.
  ☆90Updated last year
• sydney-machine-learning / Bayesianneuralnetworks-MCMC-tutorial
  Bayesian neural networks via MCMC: tutorial
  ☆56Updated 8 months ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆42Updated 11 months ago
• philipphennig / NumericsOfML
  Notes for the Numerics of Machine Learning Lecture Course at the University of Tübingen
  ☆210Updated last year
• AaltoML / BayesNewton
  Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
  ☆233Updated last year
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 2 years ago
• mvaldenegro / keras-uncertainty
  Utilities to perform Uncertainty Quantification on Keras Models
  ☆117Updated last year
• wjmaddox / online_gp
  Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"
  ☆62Updated 4 years ago
• grasool / Gaussian-Processes
  Introduction to Gaussian Processes
  ☆29Updated 7 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆89Updated 4 years ago
• rbardenet / bml-course
  Public repo for course material on Bayesian machine learning at ENS Paris-Saclay and Univ Lille
  ☆88Updated 4 months ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆127Updated 9 months ago
• tensorchiefs / dl_book
  legend
  ☆205Updated last year
• TorchUQ / torchuq
  A library for uncertainty quantification based on PyTorch
  ☆121Updated 3 years ago
• jejjohnson / uncertain_gps
  Exploring how to to deal with uncertain inputs with gaussian process regression models.
  ☆27Updated 4 years ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆32Updated last year
• gpschool / gpss20
  Gaussian Process and Uncertainty Quantification Summer School 2020
  ☆33Updated 2 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆57Updated 4 years ago
• IBM / UQ360
  Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty i…
  ☆267Updated 2 months ago
• aterenin / phdthesis
  Gaussian Processes and Statistical Decision-making in Non-Euclidean Spaces
  ☆199Updated 3 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆67Updated 5 months ago
• AaltoML / spatio-temporal-GPs
  Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'
  ☆47Updated 3 years ago
• brendanhasz / probflow
  A Python package for building Bayesian models with TensorFlow or PyTorch
  ☆176Updated 2 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆52Updated 5 years ago
• AaltoML / kalman-jax
  Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX
  ☆100Updated 2 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 3 years ago
• fonnesbeck / gp_regression
  A Primer on Gaussian Processes for Regression Analysis (PyData NYC 2019)
  ☆165Updated 3 years ago