Jin A Lee, Young Ran Kweon
[Factors affecting social competence in school-aged children according to alcohol consumption by parents']
Journal of Korean Academy of Nursing
transformers widely used deep learning architectures existing transformers mostly designed sequences texts time series images videos graphs paper proposes novel transformer model massive million point samples continuous space data ubiquitous environment sciences eg sensor observations numerical simulations eg particleladen flow astrophysics locationbased services eg pois trajectories however designing transformer massive spatial points nontrivial due several challenges including implicit longrange multiscale dependency irregular points continuous space nonuniform point distribution potential high computational costs calculating allpair attention across massive points risks overconfident predictions due varying point density address challenges propose new hierarchical spatial transformer model includes multiresolution representation learning within quadtree hierarchy efficient spatial attention via coarse approximation also design uncertainty quantification branch estimate prediction confidence related input feature noise point sparsity provide theoretical analysis computational time complexity memory costs extensive experiments realworld synthetic datasets show method outperforms multiple baselines prediction accuracy model scale one million points one nvidia a100 gpu code available httpsgithubcomspatialdatasciencegrouphst