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Deep diffusion-based forecasting of COVID-19 by incorporating network-level mobility information
Padmaksha Roy, Shailik Sarkar, Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Naren Ramakrishnan, Chang-Tien Lu
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Dynamic Multi-Context Attention Networks for Citation Forecasting of Scientific Publications
Taoran Ji, Nathan Self, Kaiqun Fu, Zhiqian Chen, Naren Ramakrishnan, Chang-Tien Lu
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SDM 21 Tutorial: Studying Spread Patterns of COVID-19 based on Spatiotemporal Data
Beiyu Lin, Xiaowei Jia, Zhiqian Chen
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Graph Learning with Kalman Filtering
Use Kalman filtering to handle uncertainty.
Fanglan Chen, 陈枳扦, Subhodip Biswas, Shuo Lei, Naren Ramakrishnan, Chang-Tien Lu
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Graph Learning with Kalman Filtering
Graph Learning on Circuits
Ues graph neural network to model circuit, and predict its encryption attribute.
陈枳扦, Gaurav Kolhe, Setareh Rafatirad, Chang-Tien Lu, Sai Manoj PD, Houman Homayoun, Liang Zhao
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Graph Learning on Circuits
Estimating the circuit de-obfuscation runtime based on graph deep learning
Zhiqian Chen, Gaurav Kolhe, Setareh Rafatirad, Chang-Tien Lu, Sai Manoj PD, Houman Homayoun, Liang Zhao
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Estimating the circuit de-obfuscation runtime based on graph deep learning
Geospatial clustering for balanced and proximal schools
Subhodip Biswas, Fanglan Chen, Andreea Sistrunk, Sathappan Muthiah, Zhiqian Chen, Nathan Self, Chang-Tien Lu, Naren Ramakrishnan
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Graph convolutional networks with kalman filtering for traffic prediction
Fanglan Chen, Zhiqian Chen, Subhodip Biswas, Shuo Lei, Naren Ramakrishnan, Chang-Tien Lu
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Graph convolutional networks with kalman filtering for traffic prediction
Incorporating domain knowledge into Memetic Algorithms for solving Spatial Optimization problems
Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Chang-Tien Lu, Naren Ramakrishnan
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Towards more accurate uncertainty estimation in text classification
Jianfeng He, Xuchao Zhang, Shuo Lei, Zhiqian Chen, Fanglan Chen, Abdulaziz Alhamadani, Bei Xiao, ChangTien Lu
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