515 citations · 791 across the 8 of their papers we have counts for
4 papers · 1 filter
Graph Transformer Networks: Learning Meta-path Graphs to Improve GNNs
Seongjun Yun, Minbyul Jeong, Sungdong Yoo +5
Graph Neural Networks (GNNs) have been widely applied to various fields due to their powerful representations of graph-structured data. Despite the success of GNNs, most existing G…
Graph Transformer Networks
Seongjun Yun, Minbyul Jeong, Raehyun Kim +2
Graph neural networks (GNNs) have been widely used in representation learning on graphs and achieved state-of-the-art performance in tasks such as node classification and link pred…
WATTNet: Learning to Trade FX via Hierarchical Spatio-Temporal Representation of Highly Multivariate Time Series
Michael Poli, Jinkyoo Park, Ilija Ilievski
Finance is a particularly challenging application area for deep learning models due to low noise-to-signal ratio, non-stationarity, and partial observability. Non-deliverable-forwa…
Predicting Multiple Demographic Attributes with Task Specific Embedding Transformation and Attention Network
Raehyun Kim, Hyunjae Kim, Janghyuk Lee +1
Most companies utilize demographic information to develop their strategy in a market. However, such information is not available to most retail companies. Several studies have been…