A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.

High-quality implementations of standard and SOTA methods on a variety of tasks.

Data Assimilation with Python: a Package for Experimental Research

🚂 Python API for Emma's Markov Model Algorithms 🚂

Probabilistic Inference on Noisy Time Series

Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)

Probabilistic Programming and Nested sampling in JAX

A Python package for building Bayesian models with TensorFlow or PyTorch

Tutorials on data assimilation (DA) and the EnKF

Modular and scalable computational imaging in Python with GPU/out-of-core computing.

Pre-trained Gaussian processes for Bayesian optimization

Python implementation of Bayesian Program Learning tools (with PyTorch)

Multiagent reinforcement learning simulation framework - Undergraduate thesis in Mechatronics Engineering at the University of Brasília

PyAutoFit: Classy Probabilistic Programming

Active Bayesian Causal Inference (Neurips'22)

[TNNLS] Bayesian Cycle-Consistent Generative Adversarial Networks via Marginalizing Latent Sampling

This is an EEG Signals Classification based on Bayesian Convolutional Neural Network (Bayesian CNNs) via Variational Inference.

A fuzzy machine learning algorithm utilizing Dempster-Shafer and Bayesian Theory

Python 3.7 version of David Barber's MATLAB BRMLtoolbox