68 citations · 133 across the 9 of their papers we have counts for
9 papers
SPGP: Structure Prototype Guided Graph Pooling
Sangseon Lee, Dohoon Lee, Yinhua Piao +1
While graph neural networks (GNNs) have been successful for node classification tasks and link prediction tasks in graph, learning graph-level representations still remains a chall…
Triangular Contrastive Learning on Molecular Graphs
MinGyu Choi, Wonseok Shin, Yijingxiu Lu +1
Recent contrastive learning methods have shown to be effective in various tasks, learning generalizable representations invariant to data augmentation thereby leading to state of t…
Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification
Yinhua Piao, Sangseon Lee, Dohoon Lee +1
Recently, graph neural networks (GNNs) have been widely used for document classification. However, most existing methods are based on static word co-occurrence graphs without sente…
Handling Long-Tail Queries with Slice-Aware Conversational Systems
Cheng Wang, Sun Kim, Taiwoo Park +5
We have been witnessing the usefulness of conversational AI systems such as Siri and Alexa, directly impacting our daily lives. These systems normally rely on machine learning mode…
TeamTat: a collaborative text annotation tool
Rezarta Islamaj, Dongseop Kwon, Sun Kim +1
Manually annotated data is key to developing text-mining and information-extraction algorithms. However, human annotation requires considerable time, effort and expertise. Given th…
BioConceptVec: creating and evaluating literature-based biomedical concept embeddings on a large scale
Qingyu Chen, Kyubum Lee, Shankai Yan +3
Capturing the semantics of related biological concepts, such as genes and mutations, is of significant importance to many research tasks in computational biology such as protein-pr…