probabilistic-modeling

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

A scalable and accurate probabilistic network configuration analyzer verifying network properties in the face of random failures.

Sum-product networks in Julia.

Distributional Gradient Boosting Machines

Trustworthy ML, scientific open source, and probabilistic systems.

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

Scalable probabilistic impact modeling

Repository to reproduce "Cascade-based Echo Chamber Detection" accepted at CIKM2022

Blackjack Notebook (bjnb): Probabilistic analysis and simulation

Diffusion Tutorials (Enhanced Chinese Edition) — A Chinese-translated and theory-enhanced version of tsmatz/diffusion-tutorials, bridging diffusion model theory (DDPM/SMLD/SDE) with practical PyTorch implementations.

Extended functionality for univariate probability distributions in PyTorch

QECops is a lightweight, open-source Monte Carlo simulation framework for studying how noise assumptions influence logical error behavior in quantum error correction (QEC). The question it seeks to answer is: How sensitive are QEC performance conclusions to the choice of noise model assumptions?

Train and evaluate probabilistic word embeddings with Python.

Football forecasting framework to simulate the FIFA World Cup using team strength modeling and probabilistic match prediction.

Tensor-Network Machine Learning with Matrix Product States, trained via a surrogate (projective) loss instead of standard negative log-likelihood