Skip to main content
College of Sciences
Department of Mathematics

Events

Events Search and Views Navigation

Event Views Navigation

Today

Differential Equations and Nonlinear Analysis Seminar: Stefania Patrizi, The University of Texas at Austin, The Discrete Dislocation Dynamics of Multiple Dislocation Loops

SAS 4201

We consider a nonlocal reaction-diffusion equation that physically arises from the classical Peierls–Nabarro model for dislocations in crystalline structures. Our initial configuration corresponds to multiple slip loop dislocations in $\mathbb R^n$, $n\geq 2$. After suitably rescaling the equation with a small phase parameter $\epsilon>0$, the rescaled solution solves a fractional Allen–Cahn equation. We show that,…

Teaching and Learning Seminar:Megan Ryals, University of Virginia,Integrating Research and Practice: The Development of Technology-Based Learning Activities in Multivariable Calculus

SAS 4201

Students often perceive Multivariable Calculus as a collection of disconnected ideas and approach problem solving in the course formulaically.  Students need help from instructors in developing spatial reasoning and making connections between symbolic computations and graphical representations. In this talk I will share how I integrated results of research on students’ learning of differential calculus…

Computational and Applied Mathematics: Anuj Abhishek, Case Western Reserve University, Operator Learning for Inverse Problems

SAS 4201

Neural operators such as Deep Operator Networks (DeepONet) and Convolutional Neural Operators (CNO) have been shown to be fairly useful in approximating an operator between two function spaces. In this talk, we will briefly review two inverse problems that arise in Medical Imaging, namely EIT and QPAT. We will also describe the relevant operator learning architectures.…

Stochastics/Discrete Analysis Seminar: Lechao Xiao, Google DeepMind, Harmonic Analysis and Theory of Deep Learning

SAS 4201

The past decade has witnessed a remarkable surge in breakthroughs in artificial intelligence (AI), with the potential to profoundly impact various aspects of our lives. However, the fundamental mathematical principles underlying the success of deep learning, the core technology behind these breakthroughs, is still far from well-understood. In this presentation, I will share some interesting…