32 citations · 57 across the 16 of their papers we have counts for
18 papers
Stable Mesh-Free Variational Radial Basis Function Approximation for Elliptic PDEs and Obstacle Problems
Tan Phuong Dong Le, Giang Tran, Hans De Sterck
We present a comprehensive study of radial basis function (RBF) approximations for elliptic and obstacle-type boundary value problems under a variational formulation. Our focus is…
Parallel-in-iteration optimization using multigrid reduction-in-time
G. H. M. Araújo, O. A. Krzysik, H. De Sterck
Standard gradient-based iteration algorithms for optimization, such as gradient descent and its various proximal-based extensions to nonsmooth problems, are known to converge slowl…
Multilevel Monte Carlo methods for stochastic convection-diffusion eigenvalue problems
Tiangang Cui, Hans De Sterck, Alexander D. Gilbert +2
We develop new multilevel Monte Carlo (MLMC) methods to estimate the expectation of the smallest eigenvalue of a stochastic convection-diffusion operator with random coefficients.…
Downlink Compression Improves TopK Sparsification
William Zou, Hans De Sterck, Jun Liu
Training large neural networks is time consuming. To speed up the process, distributed training is often used. One of the largest bottlenecks in distributed training is communicati…
Neural Lyapunov Control of Unknown Nonlinear Systems with Stability Guarantees
Ruikun Zhou, Thanin Quartz, Hans De Sterck +1
Learning for control of dynamical systems with formal guarantees remains a challenging task. This paper proposes a learning framework to simultaneously stabilize an unknown nonline…
Fast multigrid reduction-in-time for advection via modified semi-Lagrangian coarse-grid operators
H. De Sterck, R. D. Falgout, O. A. Krzysik
Many iterative parallel-in-time algorithms have been shown to be highly efficient for diffusion-dominated partial differential equations (PDEs), but are inefficient or even diverge…