MLSP-17.1
STGAT-MAD : Spatial-Temporal Graph Attention Network for Multivariate Time Series Anomaly Detection
Jun Zhan, Siqi Wang, Chengkun Wu, Detian Zeng, National University of Defense Technology, China; Xiandong Ma, Lancaster University, United Kingdom of Great Britain and Northern Ireland; Canqun Yang, National Supercomputing Center of Tianjin, China; Shilin Wang, Beijing Goldwind Smart Energy Technology Co., Ltd., China
Session:
Graph Neural Networks
Track:
Machine Learning for Signal Processing
Location:
Gather Area F
Presentation Time:
Mon, 9 May, 22:00 - 22:45 China Time (UTC +8)
Mon, 9 May, 14:00 - 14:45 UTC
Mon, 9 May, 14:00 - 14:45 UTC
Session Chair:
Zheng-Hua Tan, Aalborg University
Session MLSP-17
MLSP-17.1: STGAT-MAD : Spatial-Temporal Graph Attention Network for Multivariate Time Series Anomaly Detection
Jun Zhan, Siqi Wang, Chengkun Wu, Detian Zeng, National University of Defense Technology, China; Xiandong Ma, Lancaster University, United Kingdom of Great Britain and Northern Ireland; Canqun Yang, National Supercomputing Center of Tianjin, China; Shilin Wang, Beijing Goldwind Smart Energy Technology Co., Ltd., China
MLSP-17.2: Dual Graph Cross-domain Few-shot Learning for Hyperspectral Image Classification
Yuxiang Zhang, Wei Li, Mengmeng Zhang, Ran Tao, Beijing Institute of Technology, China
MLSP-17.3: Personalized PageRank Graph Attention Networks
Julie Choi, Amazon, United States of America
MLSP-17.4: MULTI-RELATION MESSAGE PASSING FOR MULTI-LABEL TEXT CLASSIFICATION
Muberra Ozmen, Mark Coates, McGill University, Canada; Hao Zhang, Hong Kong University of Science and Technology, Hong Kong; Pengyun Wang, Huawei Noah’s Ark Lab, China
MLSP-17.5: ADAPTIVE ATTENTION GRAPH CAPSULE NETWORK
Xiangping Zheng, Xun Liang, Bo Wu, Yuhui Guo, Hui Tang, Renmin University of China, China
MLSP-17.6: GRAPH CONVOLUTIONAL NETWORKS WITH AUTOENCODER-BASED COMPRESSION AND MULTI-LAYER GRAPH LEARNING
Lorenzo Giusti, Claudio Battiloro, Paolo Di Lorenzo, Sergio Barbarossa, Sapienza University of Rome, Italy