Overview
Civil Engineering : Introduction to spatiotemporal sensing data and general research questions (imputation, forecasting, kriging, classification, regression, anomaly detection). Overview of traditional models and techniques in modeling temporal processes, spatial processes, and spatiotemporal processes. Introduction of state-of-the-art methods for large-scale data sets, including low-rank tensor learning, spectral methods, Gaussian process regression, graph signal processing, and deep neural networks.
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Prerequisite: Permission of the instructor.
