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. Our primary analysis focuses on the top marginal personal income and corporate income tax, and their effect on top incomes and top income shares within […]
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. Such data explosion necessitates the development of novel methods for studying large, noisy, and complex data. One interesting aspect of data is its shape and […]
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 […]