Manifold Learning and Optimal Transport in Genomics Part 1

Andrew Blumberg
Columbia University
Math and CS

The purpose of this tutorial is to survey aspects of geometric data analysis that have seen substantial application in scientific inference from genomic data, with a particular focus on ideas coming from manifold learning (broadly construed) and closely related techniques from optimal transport.


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