We introduce a novel approach to predict epidemic spread over networks using total variation (TV) denoising, a signal processing technique. The study proves the consistency of TV denoising with Bernoulli noise, extending existing bounds from Gaussian noise literature. The methodology is further extended to handle incomplete observations, showcasing its effectiveness. We show that application of 1-bit total variation denoiser improves the prediction accuracy of virus spread dynamics on networks.
Personal website of Olga Klopp