arXiv Machine Learning By Minwei Zhao, Sanja Scepanovic, Stephen Law, Ivica Obadic, Cai Wu, Daniele Quercia

UST-GNN: A Unified Spatial--Topological Graph Neural Network Framework for Urban Analytics--Demonstrated through a Case Study on Urban Health Prediction

Read the original on arXiv Machine Learning →

arXiv:2504. 04739v3 Announce Type: replace Abstract: Understanding how social, demographic, environmental, and spatial factors jointly shape urban outcomes is essential for sustainable urban development and evidence-based policy.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning
Jun 5

HEIST: A Graph Foundation Model for Spatial Transcriptomics and Proteomics Data

arXiv:2506. 11152v4 Announce Type: replace-cross Abstract: Single-cell transcriptomics and proteomics have become a great source for data-driven insights into biology, enabling the use of advanced deep learning methods to understand cellular heterogeneity and gene expression at the single-cell level.

By Hiren Madhu, Jo\~ao Felipe Rocha, Tinglin Huang, Siddharth Viswanath, Smita Krishnaswamy, Rex Ying