3 papers
cs.LG2024
A data-centric approach for assessing progress of Graph Neural Networks
Tianqi Zhao, Ngan Thi Dong, Alan Hanjalic +1
Graph Neural Networks (GNNs) have achieved state-of-the-art results in node classification tasks. However, most improvements are in multi-class classification, with less focus on t…
cs.LG2023
Multi-label Node Classification On Graph-Structured Data
Tianqi Zhao, Ngan Thi Dong, Alan Hanjalic +1
Graph Neural Networks (GNNs) have shown state-of-the-art improvements in node classification tasks on graphs. While these improvements have been largely demonstrated in a multi-cla…
q-bio.QM2021
MuCoMiD: A Multitask Convolutional Learning Framework for miRNA-Disease Association Prediction
Thi Ngan Dong, Megha Khosla
Growing evidence from recent studies implies that microRNA or miRNA could serve as biomarkers in various complex human diseases. Since wet-lab experiments are expensive and time-co…