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Python implementation of Restricted Boltzmann Machine (RBM). And an example on MNIST dataset.
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow
Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events
Collection of probabilistic models and inference algorithms
Scalable inference for a generative model of astronomical images
Kalman Variational Auto-Encoder
A toolbox for differentially private data generation
Deep Markov Models
LoMRF is an open-source implementation of Markov Logic Networks
A Latent Dirichlet Allocation implementation in Python.