Henry Adams (Colorado State U)
Relationships between persistent homology, machine learning, and local geometry
Persistent homology and its vectorization techniques are popular ways to incorporate geometry in machine learning. I will survey applications arising from machine learning tasks in agent-based modeling, shape recognition, materials science, and biology. The use of topology in machine learning provides additional incentives to study the relationship between persistent homology and local geometry. Joint work with the Pattern Analysis Lab at Colorado State University.