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Functional Graph Convolutional Networks: A unified multi-task and multi-modal learning framework to facilitate health and social-care insights
This paper introduces a novel Functional Graph Convolutional Network (funGCN) framework that combines Functional Data Analysis and Graph Convolutional Networks to address the complexities of multi-task and multi-modal learning in digital health and longitudinal studies.
A new computationally efficient algorithm to solve Feature Selection for Functional Data Classification in high-dimensional spaces
This paper introduces a novel methodology for Feature Selection for Functional Classification, FSFC, that addresses the challenge of jointly performing feature selection and classification of functional data in scenarios with categorical responses and multivariate longitudinal features.
Information Flow in Graph Neural Networks: A Clinical Triage Use Case
Specifically, we propose a mathematical model that decouples the GNN connectivity from the connectivity of the graph data and evaluate the performance of GNNs in a clinical triage use case.
A recommender for the management of chronic pain in patients undergoing spinal cord stimulation
Spinal cord stimulation (SCS) is a therapeutic approach used for the management of chronic pain.
(Blue) Taxi Destination and Trip Time Prediction from Partial Trajectories
Real-time estimation of destination and travel time for taxis is of great importance for existing electronic dispatch systems.
