2024
Learning from Highly Sparse Spatio-temporal Data
NeurIPS 2024poster
Incomplete spatio-temporal data in real-world has spawned many research. However, existing methods often utilize iterative message-passing across temporal and spatial dimensions, resulting in substantial information loss and high computational cost. We provide a theoretical analysis revealing that s…