Applied Math
Organizers: ryzhik [at] stanford.edu (Lenya Ryzhik) & lexing [at] stanford.edu (Lexing Ying)
For more information and access to abstracts, click here.
Upcoming Events
The advent of generative AI has turbocharged the development of a myriad of commercial applications, and it has slowly started to permeate to scientific computing. In this talk we discussed how recasting the formulation of old and new problems within a probabilistic approach opens the door to…
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An interesting phenomenon in optics is that it is possible to see a personbehind a shower curtain better than that person can see us. This effect hasbeen referred to as the shower curtain effect.We address the challenge of giving a mathematical description of thisphenomenon. In addition, we…
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Past Events
In this talk, we shall discuss our recent work which shows that in the periodic homogenization of viscous HJ equations in any spatial dimension the effective Hamiltonian does not necessarily inherit the quasiconvexity property (in the momentum variables) of the original Hamiltonian. Moreover,…
This talk will discuss some nontrivial but often pleasant effects of large learning rates, which are commonly used in machine learning practice for improved empirical performances, but defy traditional theoretical analyses. I will first quantify how large learning rates can help gradient descent…
This presentation first discusses the derivation of radiative transfer equations for acoustic waves propagating in a randomly fluctuating half-space in the weak-scattering regime, and the study of boundary effects through an asymptotic analysis of the Wigner transform of the…
In recent years, researchers have developed a number of fast, randomized algorithms for linear algebra problems. But for widespread deployment of these methods, speed is not enough. To safely incorporate randomized algorithms into general-purpose linear algebra software, we need algorithms which…
This talk discusses the unstructured sparse recovery problems of a general form. The task is to recover the spike locations and weights of an unknown sparse signal from a collection of its unstructured observations. Examples include rational approximation, spectral function estimation, Fourier…
Degree-d multivariate polynomials over small finite fields are of central importance in theoretical computer science. And yet they retain many mysteries; for example, their Fourier spectra are very poorly understood. We will discuss the so-called "Fourier growth" of such functions…
I will present fast practical algorithms for approximate semidefinite programming (SDP) based on regularization by the von Neumann entropy. These approaches are based on a dual formulation of the regularized problem, and dual updates are computed using randomized trace estimators.…
The singularity formation problem is a central question in fluid dynamics, and it is still widely open for several fundamental models, including the 3d incompressible Euler equations. In this talk, I will first review the singularity formation problem, describing how particle transport poses the…
The large-scale rheology of random suspensions aims at describing how suspensions of small but many objects influence (sometimes drastically) a fluid flow. In physics this is the realm of complex fluids, with well-established phenomenological models. The derivation of such models from the…
Placing a two-dimensional lattice on another with a small rotation gives rise to periodic “moiré” patterns on a superlattice scale much larger than the original lattice. The Bistritzer-MacDonald (BM) model attempts to capture the electronic properties of twisted bilayer graphene (TBG) by…