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eess.SP2025
Time-Varying Graph Learning with Constraints on Graph Temporal Variation
Haruki Yokota, Koki Yamada, Yuichi Tanaka +1
We propose a novel framework for learning time-varying graphs from spatiotemporal measurements. Given an appropriate prior on the temporal behavior of signals, our proposed method…
eess.SP2024
Edge Sampling of Graphs: Graph Signal Processing Approach With Edge Smoothness
Kenta Yanagiya, Koki Yamada, Yasuo Katsuhara +2
Finding important edges in a graph is a crucial problem for various research fields, such as network epidemics, signal processing, machine learning, and sensor networks. In this pa…