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
  ☆176Updated 4 months ago
• TyXe-BDL / TyXe
  ☆154Updated 3 years ago
• probabilisticai / probai-2022
  Materials of the Nordic Probabilistic AI School 2022.
  ☆179Updated 3 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆43Updated last year
• probabilisticai / probai-2023
  Materials of the Nordic Probabilistic AI School 2023.
  ☆91Updated 2 years ago
• philipphennig / NumericsOfML
  Notes for the Numerics of Machine Learning Lecture Course at the University of Tübingen
  ☆221Updated last year
• grasool / Gaussian-Processes
  Introduction to Gaussian Processes
  ☆29Updated 7 years ago
• TorchUQ / torchuq
  A library for uncertainty quantification based on PyTorch
  ☆122Updated 3 years 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.
  ☆240Updated last year
• rbardenet / bml-course
  Public repo for course material on Bayesian machine learning at ENS Paris-Saclay and Univ Lille
  ☆91Updated 8 months ago
• sydney-machine-learning / Bayesianneuralnetworks-MCMC-tutorial
  Bayesian neural networks via MCMC: tutorial
  ☆58Updated last year
• RaulPL / awesome-gaussian-processes
  A curated list of resources for learning Gaussian Processes
  ☆41Updated 4 years ago
• jejjohnson / gp_model_zoo
  Literature and light wrappers for gaussian process models.
  ☆47Updated 4 years ago
• mvaldenegro / keras-uncertainty
  Utilities to perform Uncertainty Quantification on Keras Models
  ☆119Updated last year
• wjmaddox / online_gp
  Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"
  ☆64Updated 4 years ago
• probml / rebayes
  Recursive Bayesian Estimation (Sequential / Online Inference)
  ☆59Updated last year
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆90Updated 5 years ago
• AaltoML / kalman-jax
  Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX
  ☆102Updated 2 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 3 years ago
• AaltoML / spatio-temporal-GPs
  Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'
  ☆47Updated 3 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆58Updated 4 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆53Updated 5 years ago
• probml / probml-notebooks
  Notebooks for "Probabilistic Machine Learning" book
  ☆202Updated 3 years ago
• jejjohnson / uncertain_gps
  Exploring how to to deal with uncertain inputs with gaussian process regression models.
  ☆27Updated 4 years ago
• pyhopper / pyhopper
  PyHopper is a hyperparameter optimizer, made specifically for high-dimensional problems arising in machine learning research.
  ☆86Updated last year
• probabilisticai / probai-2021
  Materials of the Nordic Probabilistic AI School 2021.
  ☆93Updated 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…
  ☆266Updated last month
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆127Updated last year
• pierresegonne / VINF
  Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
  ☆25Updated 5 years ago
• brendanhasz / probflow
  A Python package for building Bayesian models with TensorFlow or PyTorch
  ☆176Updated 3 years ago