The Interplay of Demographic Variables and Social Distancing Scores in Deep Prediction of U.S. COVID-19 Cases*
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Jianqing Fan | Francesca Tang | Yang Feng | Hamza Chiheb | Jianqing Fan | Yang Feng | Francesca Tang | Hamza Chiheb
[1] Jianqing Fan,et al. ENTRYWISE EIGENVECTOR ANALYSIS OF RANDOM MATRICES WITH LOW EXPECTED RANK. , 2017, Annals of statistics.
[2] A. Rinaldo,et al. Consistency of spectral clustering in stochastic block models , 2013, 1312.2050.
[3] Per Block,et al. Demographic science aids in understanding the spread and fatality rates of COVID-19 , 2020, Proceedings of the National Academy of Sciences.
[4] Emmanuel Abbe,et al. Community detection and stochastic block models: recent developments , 2017, Found. Trends Commun. Inf. Theory.
[5] Yang Liu,et al. Early dynamics of transmission and control of COVID-19: a mathematical modelling study , 2020, The Lancet Infectious Diseases.
[6] Yi Li,et al. Estimation of time-varying reproduction numbers underlying epidemiological processes: A new statistical tool for the COVID-19 pandemic , 2020, PloS one.
[7] Michael Y. Li,et al. Why is it difficult to accurately predict the COVID-19 epidemic? , 2020, Infectious Disease Modelling.
[8] Alexander Wong,et al. COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images , 2020, Scientific reports.
[9] Yang Feng,et al. Local quasi-likelihood with a parametric guide. , 2009, Annals of statistics.
[10] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[11] K. Yuen,et al. Clinical Characteristics of Coronavirus Disease 2019 in China , 2020, The New England journal of medicine.
[12] Hannah R. Meredith,et al. The incubation period of 2019-nCoV from publicly reported confirmed cases: estimation and application , 2020 .
[13] Carey E. Priebe,et al. Consistent Adjacency-Spectral Partitioning for the Stochastic Block Model When the Model Parameters Are Unknown , 2012, SIAM J. Matrix Anal. Appl..
[14] Ulrike von Luxburg,et al. A tutorial on spectral clustering , 2007, Stat. Comput..
[15] Liangrong Peng,et al. Epidemic analysis of COVID-19 in China by dynamical modeling , 2020, medRxiv.
[16] Jingmin Xin,et al. Predicting COVID-19 in China Using Hybrid AI Model , 2020, IEEE Transactions on Cybernetics.
[17] G. Lugosi,et al. Community Detection in Partial Correlation Network Models , 2017, Journal of Business & Economic Statistics.
[18] Wenyu Liu,et al. Deep Learning-based Detection for COVID-19 from Chest CT using Weak Label , 2020, medRxiv.
[19] S. Wasserman,et al. Stochastic a posteriori blockmodels: Construction and assessment , 1987 .
[20] Bin Yu,et al. Spectral clustering and the high-dimensional stochastic blockmodel , 2010, 1007.1684.
[21] Sivaraman Balakrishnan,et al. Noise Thresholds for Spectral Clustering , 2011, NIPS.
[22] Minge Xie,et al. Confidence Distributions and a Unifying Framework for Meta-Analysis , 2011 .
[23] M. Xiong,et al. Artificial Intelligence Forecasting of Covid-19 in China , 2020, International Journal of Educational Excellence.
[24] Jagath C. Rajapakse,et al. Fitting networks models for functional brain connectivity , 2017, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).
[25] F. Piazza,et al. Analysis and forecast of COVID-19 spreading in China, Italy and France , 2020, Chaos, Solitons & Fractals.
[26] B. Hagberg,et al. CLINICAL CHARACTERISTICS , 1972 .
[27] W. Liang,et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions , 2020, Journal of thoracic disease.
[28] Jiashun Jin,et al. FAST COMMUNITY DETECTION BY SCORE , 2012, 1211.5803.
[29] P. Klepac,et al. Early dynamics of transmission and control of COVID-19: a mathematical modelling study , 2020, The Lancet Infectious Diseases.
[30] M. R. Brito,et al. Connectivity of the mutual k-nearest-neighbor graph in clustering and outlier detection , 1997 .
[31] Pierre Magal,et al. Predicting the cumulative number of cases for the COVID-19 epidemic in China from early data , 2020, medRxiv.
[32] M. Kraemer,et al. Preparedness and vulnerability of African countries against importations of COVID-19: a modelling study , 2020, The Lancet.
[33] Michael I. Jordan,et al. On Spectral Clustering: Analysis and an algorithm , 2001, NIPS.
[34] Regina Y. Liu,et al. iFusion: Individualized Fusion Learning , 2020, Journal of the American Statistical Association.
[35] Jitendra Malik,et al. Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[36] Chuansheng Chen,et al. An Early Examination: Psychological, Health, and Economic Correlates and Determinants of Social Distancing Amidst COVID-19 , 2020, Frontiers in Psychology.
[37] Kathryn B. Laskey,et al. Stochastic blockmodels: First steps , 1983 .
[38] Jianqing Fan,et al. Estimating Number of Factors by Adjusted Eigenvalues Thresholding , 2019, Journal of the American Statistical Association.
[39] Rebecca A Betensky,et al. Accounting for incomplete testing in the estimation of epidemic parameters , 2020, medRxiv.
[40] Jingchun Chen,et al. Detecting functional modules in the yeast protein-protein interaction network , 2006, Bioinform..