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aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
data-science machine-learning statistics deep-learning tensorflow bayesian-methods neural-networks probabilistic-programming
Probabilistic reasoning and statistical analysis in TensorFlow
data-science machine-learning statistics deep-learning tensorflow bayesian-methods neural-networks probabilistic-programming
Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
Bayesian Data Analysis course at Aalto
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
python machine-learning time-series orbit regression pytorch forecast bayesian-methods forecasting probabilistic-programming bayesian stan arima regression-models probabilistic bayesian-statistics pyro changepoint pystan exponential-smoothing
Notebooks about Bayesian methods for machine learning
machine-learning bayesian-methods gaussian-processes bayesian-optimization bayesian-machine-learning variational-autoencoder
High-quality implementations of standard and SOTA methods on a variety of tasks.
data-science machine-learning statistics deep-learning tensorflow bayesian-methods neural-networks probabilistic-programming
A simple probabilistic programming language.
data-science machine-learning statistics deep-learning tensorflow bayesian-methods neural-networks probabilistic-programming
A collection of Bayesian data analysis recipes using PyMC3
notebook bayesian-methods neural-networks bayesian bayesian-inference bayesian-data-analysis bayesian-statistics bayesian-analysis treatment-groups
Data Assimilation with Python: a Package for Experimental Research
chaos bayesian-methods particle-filter kalman-filtering data-assimilation enkf state-estimation bayesian-filter kalman
rstanarm R package for Bayesian applied regression modeling
r bayesian-methods rstan bayesian multilevel-models bayesian-inference stan r-package rstanarm bayesian-data-analysis bayesian-statistics statistical-modeling
🚂 Python API for Emma's Markov Model Algorithms 🚂
python markov-model hmm time-series analysis molecular-dynamics bayesian-methods tica hidden-markov-model markov-state-model umbrella-sampling mbar kinetic-modeling molecular-modeling
🐢 bayesAB: Fast Bayesian Methods for A/B Testing
Probabilistic Programming and Nested sampling in JAX
bayesian-methods scientific-computing probabilistic-programming nested-sampling model-comparison bayesian-computing jax scientific-machine-learning
Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.
julia julia-language bayesian-methods bayesian bayesian-inference hamiltonian-monte-carlo bayesian-statistics hybrid-monte-carlo
Probabilistic Inference on Noisy Time Series
Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
kernel deep-learning paper regression uncertainty bayesian-methods classification kernel-methods one-shot-learning uncertainty-quantification gaussian-processes kernels meta-learning shot-learning deep-kernel-learning few-shot-learning gpytorch
shinystan R package and ShinyStan GUI
r bayesian-methods bayesian bayesian-inference stan r-package shiny-apps statistical-graphics mcmc bayesian-data-analysis bayesian-statistics
The base NIMBLE package for R
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