79 citations · 187 across the 16 of their papers we have counts for
6 papers · 1 filter
HGV4Risk: Hierarchical Global View-guided Sequence Representation Learning for Risk Prediction
Youru Li, Zhenfeng Zhu, Xiaobo Guo +3
Risk prediction, as a typical time series modeling problem, is usually achieved by learning trends in markers or historical behavior from sequence data, and has been widely applied…
Multi-modal Graph Learning for Disease Prediction
Shuai Zheng, Zhenfeng Zhu, Zhizhe Liu +4
Benefiting from the powerful expressive capability of graphs, graph-based approaches have been popularly applied to handle multi-modal medical data and achieved impressive performa…
Multi-modal Graph Learning for Disease Prediction
Shuai Zheng, Zhenfeng Zhu, Zhizhe Liu +3
Benefiting from the powerful expressive capability of graphs, graph-based approaches have achieved impressive performance in various biomedical applications. Most existing methods…
Adversarial Graph Disentanglement
Shuai Zheng, Zhenfeng Zhu, Zhizhe Liu +2
A real-world graph has a complex topological structure, which is often formed by the interaction of different latent factors. However, most existing methods lack consideration of t…
Convolutional Prototype Learning for Zero-Shot Recognition
Zhizhe Liu, Xingxing Zhang, Zhenfeng Zhu +3
Zero-shot learning (ZSL) has received increasing attention in recent years especially in areas of fine-grained object recognition, retrieval, and image captioning. The key to ZSL i…
EA-LSTM: Evolutionary Attention-based LSTM for Time Series Prediction
Youru Li, Zhenfeng Zhu, Deqiang Kong +2
Time series prediction with deep learning methods, especially long short-term memory neural networks (LSTMs), have scored significant achievements in recent years. Despite the fact…