Title: How well do neurons, humans, and artificial neural networks predict? Abstract: Sensory prediction is thought to be vital to organisms, but few studies have tested how well organisms and parts of organisms efficiently predict their sensory input in an information-theoretic sense. In this talk, we report results on how well cultured neurons ("brain in […]
Title: TBD Abstract: TBD
Title: Mathematical models studying the effectiveness of control strategies for malaria Abstract: According to the 2023 World Malaria Report: Nearly half the world's population lives in areas at risk of […]
Title: Designing Robust Networks of Coupled Phase Oscillators with Applications to the High-Voltage Electric Grid Abstract: A network is any collection of objects, called nodes, in which some pairs of […]
Title: Renormalization and wild attractors for Fibonacci maps Abstract: A Fibonacci map is a piecewise defined map of a subset of an interval I onto I with a unique critical […]
Title: Smooth non-decaying solutions to the 2D dissipative quasi-geostrophic equations Abstract: In this talk we explore the two-dimensional dissipative surface quasi-geostrophic (SQG) equation with fractional diffusion of order 2α for […]
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 quotient space of orbits. Our embedding relies on subsets of sorted coorbits with respect to chosen window vectors. Our main injectivity results examine the conditions […]
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. […]
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 […]
Title: Randomly pivoted Cholesky: Fast, accurate matrix approximation for scientific machine learning Abstract: Low-rank approximation of positive semidefinite matrices is a basic problem in computational mathematics, with many applications to […]
Title: Erlang-Distributed SEIR Epidemical Models Abstract: We examine the effects of different dynamics in epidemiological models, focusing on two key approaches. The first model incorporates reaction-diffusion dynamics, where susceptible individuals […]
