TY - GEN
T1 - Emerging Trends in Graph WaveNet Research
AU - Song, Seungyeop
AU - Seol, Kihyun
AU - Lee, Yerin
AU - Park, Heejae
AU - Park, Laihyuk
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Graph Neural Networks (GNNs) have been developed to learn the spatial and temporal patterns inherent in graph-structured data, patterns that are challenging to model with traditional machine learning methods. GNNs excel at capturing complex relationships and dependencies between nodes in a graph. However, most existing GNN-based methods depend on a fixed graph structure to capture spatial dependencies. To address this limitation, Graph WaveNet was proposed, introducing a self-adaptive adjacency matrix to overcome the constraints of fixed graph structures. In this paper, we delve into the architecture of Graph WaveNet and examine its emerging research trends.
AB - Graph Neural Networks (GNNs) have been developed to learn the spatial and temporal patterns inherent in graph-structured data, patterns that are challenging to model with traditional machine learning methods. GNNs excel at capturing complex relationships and dependencies between nodes in a graph. However, most existing GNN-based methods depend on a fixed graph structure to capture spatial dependencies. To address this limitation, Graph WaveNet was proposed, introducing a self-adaptive adjacency matrix to overcome the constraints of fixed graph structures. In this paper, we delve into the architecture of Graph WaveNet and examine its emerging research trends.
KW - archi-tecture
KW - Graph neural networks
KW - Graph WaveNet
KW - research trends
UR - http://www.scopus.com/inward/record.url?scp=85217672840&partnerID=8YFLogxK
U2 - 10.1109/ICTC62082.2024.10826695
DO - 10.1109/ICTC62082.2024.10826695
M3 - Conference contribution
AN - SCOPUS:85217672840
T3 - International Conference on ICT Convergence
SP - 734
EP - 735
BT - ICTC 2024 - 15th International Conference on ICT Convergence
PB - IEEE Computer Society
T2 - 15th International Conference on Information and Communication Technology Convergence, ICTC 2024
Y2 - 16 October 2024 through 18 October 2024
ER -