Computational Intelligence group

MBCTree

An MBCTree is a classification tree with multi-dimensional Bayesian network classifiers in the leaves

gmat

R package for graphically constrained correlation matrices

species-compare-electro-morpho

species-compare-morpho

Bayesian networks for inter-species comparison

species-compare-synapses

chol-inv

Exploring the inverse Cholesky factor

Class-DBN

Experimental implementation of a hybrid model between several classifier models and a DBN model. The classifier will perform classification tasks while the DBN forecasts the state vector.

covchol

dbnR

Gaussian dynamic Bayesian networks structure learning and inference based on the bnlearn package

EDA_QAOA

VQAs ansatz parameter optimization with EDAs

EDAspy

Estimation of Distribution algorithms Python package

gardenr

Easily access the gardener's classification labels for interneurons

ggmsim

Experiments for simulation of covariance and concentration graph matrices

GLSL

HFCM

High-order fuzzy cognitive maps for multivariate data forecasting in Python 3.8.

HSPBN-Experiments

incremental-latent-forests

IEEE Access - Incremental learning of latent forests

KDE-AMD

Kernel Density Estimation - Anomaly Movement Detector

kTsnn

Implementation in Keras of time delay neural network (TDNN), convolutional recurrent neural networks (CRNN) and long short-term memory networks (LSTM) for short and long-term forecasting of time series.

mtDBN

Experimental implementation of model tree dynamic Bayesian networks, mtDBN in short

Multi-CTBNCs

Tool for learning and applying multi-dimensional continuous-time Bayesian network classifiers.

natPSOHO

Natural Encoding Particle Swarm Optimization Higher-Order Dynamic Bayesian Network Structure Learning in R

neurostrplus

Computes neuronal morphometrics

parkinson-subtypes

Scientific Reports - Identifying Parkinson's disease subtypes with motor and non-motor symptoms via model-based multi-partition clustering

PyBNesian

PyBNesian is a Python package that implements Bayesian networks.

QIEDA

Quantum-inspired Estimation of Distribution Algorithm (QIEDA) to solve the Traveling Salesman Problem. Presented in IEEE Congress on Evolutionary Computation

rcor

Experiments for uniform simulation of correlation matrices

SPBN-Experiments

This repository contains the experiments for "Semiparametric Bayesian Networks."

SPEDA

Semi-parametric Estimation of Distribution algorithm

TS_Transformation_FS

Time Series Transformations Feature Selection with Estimation of Distribution Algorithms