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brancher

A python library for stochastic variational inference and differentiable probabilistic programming

brancher-1

A user-centered Python package for differentiable probabilistic inference

brancher_chainer_backend

Brancher with Chainer backend. Brancher is a python library for stochastic variational inference and differentiable probabilistic programming. This version based on chainer is functional but it is not currently maintained.

calculusteachingmaterial

Material for teaching calculus in the Bachelor in AI at Radboud university.

cascadingflow

Automatic structured variational inference with cascading flows

functional-gp-analysis-in-python

A python toolbox for GP analysis written in a functional programming style

gp-cake-project

Bayesian Effective Connectivity

kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

locallycoupledgp

A flexible implementation of the locally coupled GP analysis

neuralensembleforecaster

Sample based forecasting with Kernel Mixture Networks

probabilistic-deep-learning

tayloralgebra

A simple package for algebraic manipulation of Taylor series. It allows to sum, multiply, divide and compose Taylor series automatically.

v130

Proceedings of AISTATS 2021

wasserstein-gan-on-mnist

This is a simple Chainer implementation of the Wasserstein GAN on MNIST digits.