13 citations · 36 across the 13 of their papers we have counts for
3 papers · 1 filter
STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization
Nikos Kargas, Cheng Qian, Nicholas D. Sidiropoulos +3
Accurate prediction of the transmission of epidemic diseases such as COVID-19 is crucial for implementing effective mitigation measures. In this work, we develop a tensor method to…
SWIFT: Scalable Wasserstein Factorization for Sparse Nonnegative Tensors
Ardavan Afshar, Kejing Yin, Sherry Yan +4
Existing tensor factorization methods assume that the input tensor follows some specific distribution (i.e. Poisson, Bernoulli, and Gaussian), and solve the factorization by minimi…
STAN: Spatio-Temporal Attention Network for Pandemic Prediction Using Real World Evidence
Junyi Gao, Rakshith Sharma, Cheng Qian +5
Objective: The COVID-19 pandemic has created many challenges that need immediate attention. Various epidemiological and deep learning models have been developed to predict the COVI…