Applied Math Seminar – Xiang Ma, Grand View University
231 Gordon Palmer HallApplications of Atomic Force Microscope in Biological and Biomedical Research Abstract: In this seminar, two examples will be presented to illustrate how a modern instrument, atomic force microscope (AFM), can be applied to solve challenging problems in the biological and biomedical field. In the first example, AFM was used to perform nanoindentation on viruses to
Undergraduate Tea
302 Gordon Palmer HallAWM General Body Meeting
346 Gordon Palmer Hall 505 Hackberry Lane, Tuscaloosa, AL, United StatesApplied Math Seminar – Duy Nguyen (Marist College)
346 Gordon Palmer Hall 505 Hackberry Lane, Tuscaloosa, AL, United StatesTitle : Nonparametric density estimation by B-spline duality Abstract: In this talk, we propose a new nonparametric density estimator derived from the theory of frames and Riesz bases. In particular, we propose the so-called bi-orthogonal density estimator based on the class of B-splines and derive its theoretical properties, including the asymptotically optimal choice of bandwidth.
Analysis Seminar – Simon Bortz (University of Washington)
346 Gordon Palmer Hall 505 Hackberry Lane, Tuscaloosa, AL, United StatesTitle: Sobolev contractivity of the gradient flow maximal function Abstract: In 2013, Carneiro and Svaiter showed that the heat flow maximal function is contractive in $\dot{W}^{1,2}(\mathbb{R}^n)$ for $W^{1,2}(\mathbb{R}^n)$ functions. In other words, if $K_t$ is the heat kernel then $u_*(x) = \sup_{t > 0} (K_t \ast |f|)(x)$ for some $f \in W^{1,2}(\mathbb{R}^n)$ then $\|\nabla u_*\|_{L^2(\mathbb{R}^n)}
Algebra/Topology Seminar – Kyungyong Lee, University of Alabama
206 Gordon Palmer Hall 505 Hackberry Lane, Tuscaloosa, AL, United StatesTitle: Introduction to cluster algebras
AWM Actuarial Talk
230 Gordon Palmer Hall 505 Hackberry Lane, AL, United StatesApplied Math Seminar – Sergei V. Gleyzer, University of Alabama
346 Gordon Palmer Hall 505 Hackberry Lane, Tuscaloosa, AL, United StatesTitle: The Interplay between Deep Learning and Physics Abstract: In my talk, I will discuss the interplay of deep learning and physics. I will focus on both foundational and applied topics, including examples of machine learning applications in high-energy physics. I will discuss interpretability, learning methodology, end-to-end learning, incorporation of physical laws in model building
Analysis Seminar – David Cruz-Uribe (University of Alabama)
346 Gordon Palmer Hall 505 Hackberry Lane, Tuscaloosa, AL, United StatesTitle: Matrix Ap weights, degenerate Sobolev spaces, and mappings of finite distortion of finite distortion.