Graph and Algebraic Signal Processing Basics for Computational Biology
Offered By: Computational Genomics Summer Institute CGSI via YouTube
Course Description
Overview
Explore graph and algebraic signal processing fundamentals for computational biology in this 29-minute conference talk by Smita Krishnaswamy at the Computational Genomics Summer Institute (CGSI). Delve into key concepts and applications, drawing from influential papers in the field. Gain insights into graph signal processing, geometric scattering for graph data analysis, and algebraic signal processing theory. Learn how these advanced techniques can be applied to solve complex problems in computational biology and genomics research.
Syllabus
Smita Krishnaswamy | Graph and Algebraic Signal Processing Basics for Computational Biology | CGSI23
Taught by
Computational Genomics Summer Institute CGSI
Related Courses
Graph Signal Processing for Neuroimaging - When Anatomy Meets ActivityIEEE Signal Processing Society via YouTube Graph Constructions for Machine Learning Applications - New Insights and Algorithms
IEEE Signal Processing Society via YouTube Data-Driven Discovery of Linear Dynamical Systems Over Graphs via Dynamical Sampling
Fields Institute via YouTube Signal Processing on Graphs and Complexes
IEEE Signal Processing Society via YouTube Connecting the Dots - Leveraging GSP to Learn Graphs From Nodal Observations
IEEE Signal Processing Society via YouTube