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)

A Python package for building Bayesian models with TensorFlow or PyTorch

Probabilistic Programming and Nested sampling in JAX

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.

Implementation of Bayesian Personalized Ranking (BPR) for Multiple Feedback Channels

Python 3.7 version of David Barber's MATLAB BRMLtoolbox