Forecasting Irregularly Sampled Time Series using Graphs

1 code implementation • 22 May 2023 • Vijaya Krishna Yalavarthi, Kiran Madhusudhanan, Randolf Sholz, Nourhan Ahmed, Johannes Burchert, Shayan Jawed, Stefan Born, Lars Schmidt-Thieme

Forecasting irregularly sampled time series with missing values is a crucial task for numerous real-world applications such as healthcare, astronomy, and climate sciences.

Astronomy Multivariate Time Series Forecasting +1