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cs.LG2026
Multi-Source Wasserstein Distributionally Robust Graph Learning
Chuansen Peng, Yifan Xia, Jinshan Zhong +1
Reconstructing complex network topologies from data is a fundamental challenge in cybernetics and graph signal processing, with applications in neuroscience, sensor, and social net…
cs.LG2026
Dynamic Elliptical Graph Factor Models via Riemannian Optimization with Geodesic Temporal Regularization
Chuansen Peng, Xiaojing Shen
Inferring time-varying graph structures from high-dimensional nodal observations is a fundamental problem arising in neuroscience, finance, climatology, and beyond. Two intrinsic c…
cs.LG2024
Network Topology Inference from Smooth Signals Under Partial Observability
Chuansen Peng, Hanning Tang, Zhiguo Wang +1
Inferring network topology from smooth signals is a significant problem in data science and engineering. A common challenge in real-world scenarios is the availability of only part…