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Yusuf Yigit Pilavci

2 accepted papers

2020

Smoothing Graph Signals via Random Spanning Forests

ICASSP 2020accepted

Another facet of the elegant link between random processes on graphs and Laplacian-based numerical linear algebra is uncovered: based on random spanning forests, novel Monte-Carlo estimators for graph signal smoothing are proposed. These random forests are sampled efficiently via a variant of Wilson…

Cited by 0SourceScholar
2019

Spectral Graph Wavelet Transform as Feature Extractor for Machine Learning in Neuroimaging

ICASSP 2019accepted

Graph Signal Processing has become a very useful framework for signal operations and representations defined on irregular domains. Exploiting transformations that are defined on graph models can be highly beneficial when the graph encodes relationships between signals. In this work, we present the b…

Cited by 0SourceScholar