In multi-armed trials, adaptive designs are a popular way to increase estimation efficiency or identify optimal treatments. Many recent papers have proposed adaptive methods for minimizing the error of unbiased […]
A Belyĭ pair \bigl( S,\, z(w) \bigr) is a compact, connected Riemann surface S together with a rational function z \colon S \to \mathbb{P}^1(\mathbb{C}) which has at most three critical values […]
A wide variety of medical imaging methods exist for research and diagnostic procedures on the Central Nervous System (CNS), among them Magnetic Resonance Imaging (MRI) and Optical Imaging. Mathematical modeling […]
Political scientists forecast elections, not primarily to satisfy public interest, but to validate statistical models used for estimating quantities of scholarly interest. Although scholars have learned a great deal from […]
This paper examines how initial conditions shape the long-run impact of large temporary shocks on economic geography. Using WWII supply contracts in the United States, we show that temporary spending […]
Large language models (LLMs) can use examples provided in a prompt to make predictions for new queries without updating their parameters, a capability known as in-context learning. In this talk, I will explore how transformers, the architectural backbone of many LLMs, can perform nonlinear kernel ridge regression (KRR). I will first present numerical observations showing […]
Please join us for the course preview of upper division undergraduate and graduate Spring 2027 courses in the Applied Mathematical Sciences. Come hear from faculty about the exciting options this upcoming Spring in applied math, data science, probability, statistics, and financial mathematics. It’s a great opportunity to learn more, ask questions, and plan your schedule!
Permutation tests are a powerful and flexible approach to inference via resampling. As computational methods become more ubiquitous in the statistics curriculum, use of permutation tests has become more tractable. […]
