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Faïcel Chamroukhi's Projects

dect-clust icon dect-clust

DECT-CLUST: DECT image clustering and application to HNSCC tumor segmentation

flamingos icon flamingos

Functional Latent datA Models for clusterING heterogeneOus curveS

hdme icon hdme

High-Dimensional Mixtures-of-Experts: proximal Newton EM for estimation and feature selection in high-dimensional mixtures of generalised linear expert models

hmmr icon hmmr

Hidden Markov Model Regression (HMMR) for time-series segmentation

hmmr_r icon hmmr_r

Hidden Markov Model Regression (HMMR) for Times Series Segmentation

meteorits icon meteorits

Mixtures-of-ExperTs modEling for cOmplex and non-noRmal dIsTributionS

mhmmr icon mhmmr

Joint segmentation of multivariate time series with a Multiple Hidden Markov Model Regression (MHMMR)

mhmmr_m icon mhmmr_m

Joint segmentation of multivariate time-series with a Multiple Hidden Markov Model Regression (MHMMR)

mixhmm icon mixhmm

Clustering and segmentation of time series by mixture of gaussian Hidden Markov Models (MixFHMMs) and the EM algorithm

mixhmm_m icon mixhmm_m

Clustering and segmentation of heteregeneous functional data (sequential data) by mixture of gaussian Hidden Markov Models (MixFHMMs) and the EM algorithm

mixhmmr icon mixhmmr

Clustering and segmentation of time series with regime changes by mixture of Hidden Markov Model Regressions (MixFHMMR) and the EM algorithm

mixhmmr_m icon mixhmmr_m

Clustering and segmentation of heterogeneous functional data (sequential data) with regime changes by mixture of Hidden Markov Model Regressions (MixFHMMR) and the EM algorithm

mixrhlp icon mixrhlp

A flexible mixture model for simultaneous clustering and segmentation of functional data (time series). It uses the EM algorithm (or a CEM-like algorithm).

mixrhlp_m icon mixrhlp_m

Flexible Mixture modelling for simultaneous clustering and segmentation of heterogeneous functional data

mixrhlp_py icon mixrhlp_py

A flexible mixture model for simultaneous clustering and segmentation of functional data (time series). It uses the EM algorithm (or a CEM-like algorithm).

mpwr icon mpwr

Optimal joint segmentation of multivariate time-series with a Multiple Piece-Wise Regression model (MPWR)

mpwr_r icon mpwr_r

Joint segmentation of multivariate time-series with a Multiple Piece-Wise Regression model (MPWR)

mrhlp icon mrhlp

Joint segmentation of multivariate time series with a Multiple Regression model with a Hidden Logistic Process (MRHLP).

mrhlp_m icon mrhlp_m

Joint segmentation of multivariate time-series with a Multiple Regression model with a Hidden Logistic Process (MRHLP).

pwr_m icon pwr_m

Piecewise regression (PWR) for the optimal segmentation of time-series with regime changes

pwr_r icon pwr_r

Piecewise Regression (PWR) for Optimal Time Series Segmentation

rhlp icon rhlp

User-freindly and flexible algorithm for time series segmentation by a Regression model with a Hidden Logistic Process (RHLP).

rhlp_m icon rhlp_m

User-friendly and flexible algorithm for time-series segmentation by a Regression model with a Hidden Logistic Process (RHLP).

samurais icon samurais

StAtistical Models for the UnsupeRvised segmentAion of tIme-Series

snmoe icon snmoe

Skew-Normal Mixture-of-Experts: A toolbox for Non-Linear Regression and Clustering using some non-normal mixtures of experts

snmoe_m icon snmoe_m

Skew-Normal Mixture-of-Experts: A toolbox for Non-Linear Regression and Clustering using some non-normal mixtures of experts

stmoe icon stmoe

Robust modeling, density estimation and model-based clustering of heterogeneous regression data with possibly skewed and non-normal distributions using skew-t mixture of experts.

stmoe_m icon stmoe_m

Toolbox for the Skew-t mixture of experts (StMoE) model

tmoe icon tmoe

Robust Mixtures-of-Experts for Non-Linear Regression and Clustering

tmoe_m icon tmoe_m

Robust Mixtures-of-Experts modelling using the t distribution for clustering and non-linear regression for heteregenous data

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