Alternatives and similar repositories for bayesianfridge:

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

• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 2 years ago
• matt-graham / phd-thesis
  Auxiliary variable Markov chain Monte Carlo methods
  ☆10Updated 7 years ago
• taposh / forecast
  Forecasting library in python
  ☆13Updated 5 years ago
• pierresegonne / VINF
  Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
  ☆25Updated 4 years ago
• danieljtait / ladax
  Layered distributions using FLAX/JAX
  ☆10Updated 4 years ago
• chrisdxie / in-depth-VI-tutorial
  ☆11Updated 8 years ago
• didriknielsen / ds3_abi_exercises
  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018
  ☆22Updated 6 years ago
• anndvision / quince
  Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
  ☆21Updated 2 years ago
• fonnesbeck / gp_tutorial_pydata
  PyData San Luis 2017 Tutorial: An Introduction to Gaussian Processes in PyMC3
  ☆15Updated 7 years ago
• BouchardLab / pyuoi
  The Union of Intersections Framework in Python
  ☆13Updated last week
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆33Updated 9 years ago
• uber-research / vargp
  Variational Auto-Regressive Gaussian Processes for Continual Learning
  ☆21Updated 3 years ago
• LCSL / NystromCoRe
  Rudi, A., Camoriano, R. and Rosasco, L., Less is more: Nyström computational regularization. In Advances in Neural Information Processing…
  ☆12Updated 5 years ago
• ChangYong-Oh / HyperSphere
  ☆16Updated 6 years ago
• vtopt / qnstop
  Quasi-Newton Algorithm for Stochastic Optimization
  ☆10Updated 2 years ago
• fonnesbeck / PyMC3_EUSS
  Course in Probabilistic Programming in Python for the 2018 EU Summer School
  ☆23Updated 6 years ago
• microprediction / optimizer-elo-ratings
  Assigns Elo Ratings to Python Global Optimizers
  ☆22Updated 11 months ago
• kd383 / GPML_SLD
  Scalable Log Determinants for Gaussian Process Kernel Learning (https://arxiv.org/abs/1711.03481) (NIPS 2017)
  ☆18Updated 7 years ago
• big-data-lab-umbc / ensemble_causality_learning
  ☆10Updated 4 years ago
• cavaunpeu / gaussian-processes
  A thorough, straightforward, un-intimidating introduction to Gaussian processes in NumPy.
  ☆16Updated 6 years ago
• charlesmartin14 / emf-rbm
  Extended Mean Field Restricted Boltzmann Machine
  ☆17Updated 8 years ago
• rubinxin / FITBO
  Code for Fast Information-theoretic Bayesian Optimisation
  ☆16Updated 6 years ago
• alexub / jax-meta-learning
  Simple, extensible implementations of some meta-learning algorithms in Jax
  ☆9Updated 4 years ago
• cicl-stanford / csm
  Contains all materials for the paper "A counterfactual simulation model of causal judgment".
  ☆23Updated 3 years ago
• juliuskunze / cwvae-jax
  Clockwork VAEs in JAX/Flax
  ☆32Updated 3 years ago
• tansey / functionalmf
  Functional matrix factorization via Bayesian tensor filtering
  ☆13Updated 2 years ago
• nickfrosst / neural_additive_models
  stand alone Neural Additive Models, forked from google-reasearch for easy import to colab
  ☆27Updated 4 years ago
• pyro-ppl / sandbox
  Pyro models and misc examples.
  ☆19Updated 3 years ago
• AaltoML / boundary-gp
  Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features
  ☆23Updated 5 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 3 years ago