GEMS March 1st Session
This GEMS session will be facilitated by Professor Jemma Lorenat from Pitzer College. Title: Playing with the Rules of Geometries Abstract: This session will explore how a small set of rules can be used […]
This GEMS session will be facilitated by Professor Jemma Lorenat from Pitzer College. Title: Playing with the Rules of Geometries Abstract: This session will explore how a small set of rules can be used […]
We’ll first define the two-point gravitational correlators which appeared last week as descendant Gromov-Witten invariants. By request, we’ll then introduce Gromov-Witten invariants as they appear in the expository work https://arxiv.org/abs/2501.03232 and give CP^1 […]
Title: Bi-Lipschitz Invariants Abstract: Consider a finite-dimensional real vector space and a finite group acting unitarily on it. We investigate the general problem of constructing Euclidean stable embeddings of the […]
We especially welcome all undergraduates and graduate students to attend topology seminar! Speaker: Carrie Frizzell (Scripps College) Title: A Primer on Tropical Geometry Abstract: Max-plus and min-plus semifields—coined tropical semifields—appeared […]
The Claremont Topology Seminar, with funding from Pitzer College and the NSF, is pleased to sponsor the N+12th Southern California Topology Colloquium (SCTC). SCTC is a one-day conference primarily attended […]
Title: Do Taxes Affect Pre-Tax Income Inequality? Evidence from 100 Years of U.S. States Abstract: We study how U.S. state taxes have affected pre-tax income inequality during the last century. […]
We especially welcome all undergraduates and graduate students to attend topology seminar! Speaker: Iris Yoon (Wesleyan University) Title: Dowker duality, profunctors, and spectral sequences Abstract: I will present three short, […]
Speaker: Iris Yoon, Professor of Mathematics, Wesleyan University Title: How Topology Reveals Structure in Neuroscience Data Abstract: We live in an exciting time where new data is generated at an exponential rate. […]
No seminar this week due to Spring break!
Title: Learning on manifolds without manifold learning Abstract: Function approximation based on data drawn randomly from an unknown distribution is an important problem in machine learning. The manifold hypothesis assumes […]