36 citations · 154 across the 55 of their papers we have counts for
9 papers · 1 filter
Explaining Clustering of Ecological Momentary Assessment Data Through Temporal and Feature Attention
Mandani Ntekouli, Gerasimos Spanakis, Lourens Waldorp +1
In the field of psychopathology, Ecological Momentary Assessment (EMA) studies offer rich individual data on psychopathology-relevant variables (e.g., affect, behavior, etc) in rea…
Navigating WebAI: Training Agents to Complete Web Tasks with Large Language Models and Reinforcement Learning
Lucas-Andreï Thil, Mirela Popa, Gerasimos Spanakis
Recent advancements in language models have demonstrated remarkable improvements in various natural language processing (NLP) tasks such as web navigation. Supervised learning (SL)…
Exploiting Individual Graph Structures to Enhance Ecological Momentary Assessment (EMA) Forecasting
Mandani Ntekouli, Gerasimos Spanakis, Lourens Waldorp +1
In the evolving field of psychopathology, the accurate assessment and forecasting of data derived from Ecological Momentary Assessment (EMA) is crucial. EMA offers contextually-ric…
Model-based Clustering of Individuals' Ecological Momentary Assessment Time-series Data for Improving Forecasting Performance
Mandani Ntekouli, Gerasimos Spanakis, Lourens Waldorp +1
Through Ecological Momentary Assessment (EMA) studies, a number of time-series data is collected across multiple individuals, continuously monitoring various items of emotional beh…
Clustering individuals based on multivariate EMA time-series data
Mandani Ntekouli, Gerasimos Spanakis, Lourens Waldorp +1
In the field of psychopathology, Ecological Momentary Assessment (EMA) methodological advancements have offered new opportunities to collect time-intensive, repeated and intra-indi…
Using Explainable Boosting Machine to Compare Idiographic and Nomothetic Approaches for Ecological Momentary Assessment Data
Mandani Ntekouli, Gerasimos Spanakis, Lourens Waldorp +1
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…
LoGANv2: Conditional Style-Based Logo Generation with Generative Adversarial Networks
Cedric Oeldorf, Gerasimos Spanakis
Domains such as logo synthesis, in which the data has a high degree of multi-modality, still pose a challenge for generative adversarial networks (GANs). Recent research shows that…
Autoregressive Convolutional Recurrent Neural Network for Univariate and Multivariate Time Series Prediction
Matteo Maggiolo, Gerasimos Spanakis
Time Series forecasting (univariate and multivariate) is a problem of high complexity due the different patterns that have to be detected in the input, ranging from high to low fre…
Bagged Boosted Trees for Classification of Ecological Momentary Assessment Data
Gerasimos Spanakis, Gerhard Weiss, Anne Roefs
Ecological Momentary Assessment (EMA) data is organized in multiple levels (per-subject, per-day, etc.) and this particular structure should be taken into account in machine learni…