21 citations · 56 across the 7 of their papers we have counts for
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cs.LG2023
Boosting long-term forecasting performance for continuous-time dynamic graph networks via data augmentation
Yuxing Tian, Mingjie Zhu, Jiachi Luo +1
This study focuses on long-term forecasting (LTF) on continuous-time dynamic graph networks (CTDGNs), which is important for real-world modeling. Existing CTDGNs are effective for…
cs.LG2022★ 5 cited
Motif-aware temporal GCN for fraud detection in signed cryptocurrency trust networks
Song Li, Jiandong Zhou, Chong MO +3
Graph convolutional networks (GCNs) is a class of artificial neural networks for processing data that can be represented as graphs. Since financial transactions can naturally be co…
cs.LG2021
Clustered Federated Learning via Generalized Total Variation Minimization
Yasmin SarcheshmehPour, Yu Tian, Linli Zhang +1
We study optimization methods to train local (or personalized) models for decentralized collections of local datasets with an intrinsic network structure. This network structure ar…