Výsledky vyhledávání - "Ntekouli, Mandani"

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Explaining Clustering of Ecological Momentary Assessment Data Through Temporal and Feature Attention

Autor: Ntekouli, Mandani, Spanakis, Gerasimos, Waldorp, Lourens, Roefs, Anne

In the field of psychopathology, Ecological Momentary Assessment (EMA) studies offer rich individual data on psychopathology-relevant variables (e.g., affect, behavior, etc) in real-time. EMA data is collected dynamically, represented as complex mult

Externí odkaz: http://arxiv.org/abs/2405.04854

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Exploiting Individual Graph Structures to Enhance Ecological Momentary Assessment (EMA) Forecasting

Autor: Ntekouli, Mandani, Spanakis, Gerasimos, Waldorp, Lourens, Roefs, Anne

In the evolving field of psychopathology, the accurate assessment and forecasting of data derived from Ecological Momentary Assessment (EMA) is crucial. EMA offers contextually-rich psychopathological measurements over time, that practically lead to

Externí odkaz: http://arxiv.org/abs/2403.19442

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Model-based Clustering of Individuals' Ecological Momentary Assessment Time-series Data for Improving Forecasting Performance

Autor: Ntekouli, Mandani, Spanakis, Gerasimos, Waldorp, Lourens, Roefs, Anne

Through Ecological Momentary Assessment (EMA) studies, a number of time-series data is collected across multiple individuals, continuously monitoring various items of emotional behavior. Such complex data is commonly analyzed in an individual level,

Externí odkaz: http://arxiv.org/abs/2310.07491

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Clustering individuals based on multivariate EMA time-series data

Autor: Ntekouli, Mandani, Spanakis, Gerasimos, Waldorp, Lourens, Roefs, Anne

In the field of psychopathology, Ecological Momentary Assessment (EMA) methodological advancements have offered new opportunities to collect time-intensive, repeated and intra-individual measurements. This way, a large amount of data has become avail

Externí odkaz: http://arxiv.org/abs/2212.01159

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Using Explainable Boosting Machine to Compare Idiographic and Nomothetic Approaches for Ecological Momentary Assessment Data

Autor: Ntekouli, Mandani, Spanakis, Gerasimos, Waldorp, Lourens, Roefs, Anne

Previous research on EMA data of mental disorders was mainly focused on multivariate regression-based approaches modeling each individual separately. This paper goes a step further towards exploring the use of non-linear interpretable machine learnin

Externí odkaz: http://arxiv.org/abs/2204.01689

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