The epiDAMIK workshop serves as a platform for advancing the utilization of data-driven methods in the fields of epidemiology and public health research. These fields have seen relatively limited exploration of data-driven approaches compared to other disciplines. Therefore, our primary objective is to foster the growt...
Alexander Rodríguez, B. Adhikari, A. Srivastava et al.· Proceedings of the 32nd ACM...· 0 citations
Experimental results demonstrate that the coarsening technique significantly accelerates dynamic GNN training and inference without compromising predictive performance, offering a practical path toward scalable dynamic graph learning.
Hieu Vu, Rares-Mihail Neagu, B. Adhikari· Proceedings of the 32nd ACM...· 0 citations
Contrastive Conformal HGNN (CCF-HGNN) is proposed that accounts for uncertainty in hypergraph-based models by explicitly regularizing on the hypergraph structure for guaranteed and robust uncertainty estimates.
Akash Choudhuri, B. Adhikari· Proceedings of the 32nd ACM...· 0 citations
Neural representations of task-relevant sounds are emphasized when they are attended to, compared with when they are ignored. Classic markers of this modulation, such as amplitude change of event-related potentials (ERPs) and attentional modulation indices (AMIs) derived from envelope-tracking analyses, provide robust...
Jusung Ham, Ian Pope, Jinhee Kim et al.· Trends in Hearing· 0 citations
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