extremeSTM

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

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

Implementation of Peaks-over-Threshold algorithms, including POT, Stream POT (SPOT), and SPOT with Drift (DSPOT).

GHRS: Graph-based hybrid recommendation system with application to movie recommendation