Guo-Dong Xiao

AINR: attention-guided implicit neural representations for spatial domain identification in spatial transcriptomics

AINR is an end-to-end deep learning framework that models spatial transcriptomics data as a geometrically constrained continuous biological field, using a periodic sine activation function to map spatial coordinates directly to gene expression while preserving spatial smoothness without explicit adjacency matrices.