2020
Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis
ICML 2020poster
Efficient and interpretable spatial analysis is crucial in many fields such as geology, sports, and climate science. Tensor latent factor models can describe higher-order correlations for spatial data. However, they are computationally expensive to train and are sensitive to initialization, leading…