Offline policy learning aims at utilizing observations collected a priori (from either fixed or adaptively evolving behavior policies) to learn the optimal individualized decision rule in a given class.

We introduce a new class of multilevel, adaptive, dual-space methods for computing fast convolutional transforms.

I will describe recent progress related to harmonic maps: regularity, existence, free boundaries and qualitative properties.

In this talk, we consider the Christoffel transformations for skew-orthogonal polynomials and partial-skew-orthogonal polynomials.

The invariant distribution, which is characterized by the stationary Fokker-Planck equation, is an important object in the study of randomly perturbed dynamical systems.

In this mini-series of talks, we will survey some recent advances in utilizing advances in machine learning to help tackle challenging tasks in scientific computing, focusing on numerical methods for solving high dimensional partial differential equations and high dimensio

To offer unique opportunities for Secondary 4 to 5 students and Year 11 to 12 international school students to explore the fascinating world of quantum computing, the School of Science of HKUST gladly presents the on-campus summer program –