Deep universal probabilistic programming with Python and PyTorch
InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
a python framework to build, learn and reason about probabilistic circuits and tensor networks
A collection of Methods and Models for various architectures of Artificial Neural Networks
Sum-product networks in Julia.
A scalable and accurate probabilistic network configuration analyzer verifying network properties in the face of random failures.
Distributional Gradient Boosting Machines
An extension of Py-Boost to probabilistic modelling
A normalizing flow using Bernstein polynomials for conditional density estimation.
A toolbox for inference of mixture models
Extended functionality for univariate probability distributions in PyTorch
Repository to reproduce "Cascade-based Echo Chamber Detection" accepted at CIKM2022
Blackjack Notebook (bjnb): Probabilistic analysis and simulation
Train and evaluate probabilistic word embeddings with Python.
Probabilistic Programming with Python and Chainer
Materials for my course SOCI 3040, Quantitative Research Methods
The interface library for probabilistic modeling in HEP
libreMCM (libre Multi Compartment Modelling) is a free software for carrying out deterministic and probabilistic modelling.
LaTeX source code for my doctoral dissertation "Probabilistic Methods for High-Resolution Metagenomics". Available from the digital repository of the University of Helsinki at https://helda.helsinki.fi/handle/10138/349862.
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