Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving

Open-source framework for uncertainty and deep learning models in PyTorch 🌱

🧮 Bayesian networks in Python

Implementation and evaluation of different approaches to get uncertainty in neural networks

Implement PC algorithm in Python | PC 算法的 Python 实现

CNN, RNN, and Bayesian NN classification for ECG time-series (using TensorFlow in Swift and Python)

Group Emotion Recognition using deep neural networks and Bayesian classifiers.

Estimation of Distribution algorithms Python package

Linear Gaussian Bayesian Networks - Inference, Parameter Learning and Representation. 🖧

General purpose C++ library for managing discrete factor graphs

High-performance library for approximate inference on discrete Bayesian networks on GPU and CPU

This repository is a mirror. If you want to raise an issue or contact us, we encourage you to do it on Gitlab (https://gitlab.com/agrumery/aGrUM).

algorithm for study: multi-layer-perceptron, cluster-graph, cnn, rnn, restricted boltzmann machine, bayesian network

Python 3.7 version of David Barber's MATLAB BRMLtoolbox

Fast Inference of Networks from Directed Regulations

Generation of Synthetic Populations Library

My simplest implementations of common ML algorithms

Adaptive Reinforcement Learning of curious AI basketball agents

[INACTIVE] Amazingly simple to build and train various neural networks. The library is an object-oriented neural network approach (baked with Typescript), containing stateless and stateful neural network architectures.