active-bayesian-causal-inference

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 ;)

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

Probabilistic reasoning and statistical analysis in TensorFlow

Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

A modular active learning framework for Python

High-quality implementations of standard and SOTA methods on a variety of tasks.

:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions

Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

Bayesian active learning library for research and industrial usecases.