IEEE

Graph-Based Adaptive Network With Spatial-Spectral Features for Hyperspectral Unmixing

Abstract: Hyperspectral unmixing aims to extract basic material (endmember) spectra and estimate their corresponding fractions (abundances) from observed pixels in hyperspectral images (HSIs).
IEEE

Structural-Spectral Graph Convolution With Evidential Edge Learning for Hyperspectral Image Clustering

Abstract: Hyperspectral image (HSI) clustering groups pixels into clusters without labeled data, which is an important yet challenging task. For large-scale HSIs, most methods rely on superpixel ...
GitHub

Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting

@article{jin2025expressive, title={Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting}, author={Ming Jin and Guangsi Shi and Yuan-Fang Li and Bo Xiong and Tian Zhou ...
GitHub

Code for "Spectral decomposition of chemical semantics for activity cliffs-aware molecular property prediction".

Accurately predicting physicochemical and biological properties for molecules is of great significance for modern drug discovery, yet existing deep learning models often fail to emulate the holistic, ...
Frontiers

Multimodal graph neural networks in healthcare: a review of fusion strategies across biomedical domains

1 Department of Analytics, Harrisburg University of Science and Technology, Harrisburg, PA, United States 2 Department of Emergency Medicine, UMass Chan Medical School, Worcester, MA, United States ...
Frontiers

Parental autonomy support and future education planning among Chinese senior high school students: a chain mediation model integrating self-determination theory and social ...

Introduction: Parental autonomy support (PAS) has been identified as a key factor in shaping adolescents’ educational development, yet little research has examined how PAS predicts students’ future ...