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

🧮 Bayesian networks in Python

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

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. 🖧

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

General purpose C++ library for managing discrete factor graphs

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

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).

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.