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Found 6 papers, 4 papers with code
Comparative study of clustering models for multivariate time series from connected medical devices
In healthcare, patient data is often collected as multivariate time series, providing a comprehensive view of a patient's health status over time.
Model-based Clustering with Missing Not At Random Data
In this paper, we propose model-based clustering algorithms designed to handle very general types of missing data, including MNAR data.
An iterative clustering algorithm for the Contextual Stochastic Block Model with optimality guarantees
Our algorithm can be applied to general Contextual Stochastic Block Models and avoids hyperparameter tuning in contrast to previously proposed methods.
Clustering multilayer graphs with missing nodes
When these relationships have different modalities, they are better modelled by multilayer graphs where each layer is associated with one modality.
A bumpy journey: exploring deep Gaussian mixture models
The DGMM consists of stacking MFA layers, in the sense that the latent scores are no longer assumed to be drawn from a standard Gaussian, but rather are drawn from a mixture of factor analysers model.
Feature quantization for parsimonious and interpretable predictive models
For regulatory and interpretability reasons, logistic regression is still widely used.
Methodology Econometrics
