Bayesian Modeling and Probabilistic Programming in Python
- python
- statistical-analysis
- bayesian-inference
- mcmc
Repository Index
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Deep universal probabilistic programming with Python and PyTorch
- python
- pytorch
- machine-learning
- bayesian
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
- causal-inference
- machine-learning
- graphical-models
- bayesian-networks
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
- bayesian-methods
- deep-learning
- machine-learning
- data-science
Probabilistic reasoning and statistical analysis in TensorFlow
- tensorflow
- bayesian-methods
- deep-learning
- machine-learning
A highly efficient implementation of Gaussian Processes in PyTorch
- pytorch
- gaussian-processes
- gpu-acceleration
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.
Python Toolkit for Causal and Probabilistic Reasoning
- python
- bayesian-networks
- causal-inference
- causal-discovery
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.
- stan
- bayesian-inference
- bayesian
- bayesian-methods
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
- pyro
- jax
- hmc
- inference-algorithms
Bayesian inference with probabilistic programming.
- machine-learning
- probabilistic-programming
- julia-language
- artificial-intelligence
A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow
- bayesian-inference
- probabilistic-programming
- graphical-models
- generative-models
Gaussian processes framework in python
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
- python
- forecasting
- bayesian
- exponential-smoothing
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
- uncertainty
- uncertainty-quantification
- uncertainty-estimation
- uncertainty-metrics
Statistical package in Python based on Pandas
- pandas
- statistics
- anova
- effect-size
Gaussian processes in TensorFlow
- gaussian-processes
- tensorflow
- gpflow
- machine-learning
Exploratory analysis of Bayesian models with Python
- python
- bayesian
- closember
A general-purpose probabilistic programming system with programmable inference
- probabilistic-programming
- gen
- deep-learning
- bayesian
Infer.NET is a framework for running Bayesian inference in graphical models
- machine-learning
- bayesian-inference
The repository host gives no description.
A Bayesian database table for querying the probable implications of data as easily as SQL databases query the data itself. New implementation in http://github.com/probcomp/bayeslite
Python package for Bayesian Machine Learning with scikit-learn API
- python
- bayesian-machine-learning
- machine-learning
- scikit-learn
High-performance Bayesian Data Analysis on the GPU in Clojure
- clojure
- bayesian-inference
- bayesian-data-analysis
- gpu-computing