Deep universal probabilistic programming with Python and PyTorch
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Updated
May 27, 2024 - Python
Deep universal probabilistic programming with Python and PyTorch
InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
A collection of Methods and Models for various architectures of Artificial Neural Networks
Sum-product networks in Julia.
A toolbox for inference of mixture models
A normalizing flow using Bernstein polynomials for conditional density estimation.
Repository to reproduce "Cascade-based Echo Chamber Detection" accepted at CIKM2022
Probabilistic Programming with Python and Chainer
Train and evaluate probabilistic word embeddings with Python.
A scalable and accurate probabilistic network configuration analyzer verifying network properties in the face of random failures.
Distributional Gradient Boosting Machines
Extended functionality for univariate probability distributions in PyTorch
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.
An extension of Py-Boost to probabilistic modelling
The interface library for probabilistic modeling in HEP
Blackjack Notebook (bjnb): Probabilistic analysis and simulation
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