no code implementations • 2 Jun 2023 • Saghar Bagheri, Gene Cheung, Tim Eadie
Specifically, we first show that greedily removing an edge at a time that induces the minimal change in the second eigenvalue leads to a sparse graph with good GCN performance.
no code implementations • 18 Aug 2022 • Chinthaka Dinesh, Gene Cheung, Saghar Bagheri, Ivan V. Bajic
Experimental results show that our signed graph sampling method outperformed existing fast sampling schemes noticeably on various datasets.
no code implementations • 4 Aug 2022 • Saghar Bagheri, Chinthaka Dinesh, Gene Cheung, Timothy Eadie
Prediction of annual crop yields at a county granularity is important for national food production and price stability.
no code implementations • 2 Mar 2022 • Saghar Bagheri, Tam Thuc Do, Gene Cheung, Antonio Ortega
Transform coding to sparsify signal representations remains crucial in an image compression pipeline.
no code implementations • 25 Oct 2020 • Saghar Bagheri, Gene Cheung, Antonio Ortega, Fen Wang
Learning a suitable graph is an important precursor to many graph signal processing (GSP) pipelines, such as graph spectral signal compression and denoising.