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Accurately predicting individual-level infection state is of great value since its essential role in reducing the damage of the epidemic.
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Estimating the Generation Interval and Inferring the Latent Period of COVID-19 from the Contact Tracing Data
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Modeling Transmission of SARS-CoV-2 Omicron in China
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Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions
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Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence
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Nationwide Rollout Reveals Efficacy of Epidemic Control through Digital Contact Tracing
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MepoGNN: Metapopulation epidemic forecasting with graph neural networks. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases
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DeepTrace: Learning to Optimize Contact Tracing in Epidemic Networks with Graph Neural Networks
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SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data
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Toward accurate spatiotemporal covid-19 risk scores using high-resolution real-world mobility data
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Graph-flashback network for next location recommendation. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 1463–1471
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Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting
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Estimating the State of Epidemics Spreading with Graph Neural Networks
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CausalGNN: Causal-Based Graph Neural Networks for Spatio-Temporal Epidemic Forecasting
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A federated graph neural network framework for privacy-preserving personalization
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Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 4639–4647
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Contact Tracing and Epidemic Intervention via Deep Reinforcement Learning
Tao Feng, Sirui Song, Tong Xia, and Yong Li. 2023 · 2023
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Poincaré Heterogeneous Graph Neural Networks for Sequential Recommendation
Naicheng Guo, Xiaolei Liu, Shaoshuai Li, Qiongxu Ma, Kaixin Gao, Bing Han, Lin Zheng, Sheng Guo, and Xiaobo Guo. 2023 · 2023
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Decentralized collaborative learning framework for next POI recommendation
Jing Long, Tong Chen, Quoc Viet Hung Nguyen, and Hongzhi Yin. 2023 · 2023
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