Seminars

ABSTRACT Spatial-temporal data on population dynamics offer important evidence of how populations evolve over time and space, whether the populations consist of groups of living organisms, the canc...

ABSTRACT We develop a Voronoi cell-based model of epithelial cell dynamics and apply it to two different phenomena: (1) the regulation of the cornea, and (2) potential pathways for the evolution of...

ABSTRACT In the presence of closely located inclusions in elastic composite materials consisting of inclusions and a matrix of different material properties, the stress represented by the gradient ...

ABSTRACT Markov chain Monte Carlo (MCMC) is a powerful and well-known class of methods aimed to sample from probability distributions....

ABSTRACT Deep neural networks have brought transformative changes in areas such as image recognition and healthcare, yet their underlying theoretical principles remain somewhat elusive....

ABSTRACT We study the application of well-known physics-informed neural networks (PINNs) for solving non-smooth PDE-constrained optimization problems....

ABSTRACT In this talk, we discuss some recent results for photonic and quantum interacting systems....

ABSTRACT In the era of big data, the analysis of large scale text and network data has become a widely studied hot topic....

ABSTRACT We will consider a class of $n$th-order linear ordinary differential equations with a large parameter $u$....

ABSTRACT In this talk, I will present a sharp local well-posedness result for spherically symmetric solutions to quasilinear wave equations with rough initial data, when the spatial dimension is th...