3 papers
eess.SP2026
Optimal Sensor Placement via Graph-constrained Flow Matching
Feng Ji, Jingyang Dai, Wee Peng Tay +1
Optimal sensor placement is a fundamental problem in graph signal processing (GSP), where a limited number of sensors are deployed to reconstruct a continuous signal field. Existin…
cs.LG2026
Adaptive Multi-view Graph Contrastive Learning via Fractional-order Neural Diffusion Networks
Yanan Zhao, Feng Ji, Jingyang Dai +4
Graph contrastive learning (GCL) learns node and graph representations by contrasting multiple views of the same graph. Existing methods typically rely on fixed, handcrafted views-…
cs.LG2025
AODDiff: Probabilistic Reconstruction of Aerosol Optical Depth via Diffusion-based Bayesian Inference
Linhao Fan, Hongqiang Fang, Jingyang Dai +2
High-quality reconstruction of Aerosol Optical Depth (AOD) fields is critical for Atmosphere monitoring, yet current models remain constrained by the scarcity of complete training…