57 citations · 103 across the 25 of their papers we have counts for
4 papers · 1 filter
FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks
Xinyu Fu, Irwin King
Heterogeneous graph neural networks (HGNNs) can learn from typed and relational graph data more effectively than conventional GNNs. With larger parameter spaces, HGNNs may require…
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy
Yifei Zhang, Dun Zeng, Jinglong Luo +2
Trustworthy artificial intelligence (AI) technology has revolutionized daily life and greatly benefited human society. Among various AI technologies, Federated Learning (FL) stands…
Drug Synergistic Combinations Predictions via Large-Scale Pre-Training and Graph Structure Learning
Zhihang Hu, Qinze Yu, Yucheng Guo +5
Drug combination therapy is a well-established strategy for disease treatment with better effectiveness and less safety degradation. However, identifying novel drug combinations th…
Discrete Auto-regressive Variational Attention Models for Text Modeling
Xianghong Fang, Haoli Bai, Jian Li +3
Variational autoencoders (VAEs) have been widely applied for text modeling. In practice, however, they are troubled by two challenges: information underrepresentation and posterior…