3 citations · 6 across the 3 of their papers we have counts for
4 papers
Reversible Deep Learning for 13C NMR in Chemoinformatics: On Structures and Spectra
Stefan Kuhn, Vandana Dwarka, Przemyslaw Karol Grenda +1
We introduce a reversible deep learning model for 13C NMR that uses a single conditional invertible neural network for both directions between molecular structures and spectra. The…
Recent Results on Domain Decomposition Preconditioning for the High-frequency Helmholtz Equation using Absorption
I. G. Graham, E. A. Spence, E. Vainikko
In this paper we present an overview of recent progress on the development and analysis of domain decomposition preconditioners for discretised Helmholtz problems, where the precon…
Domain Decomposition preconditioning for high-frequency Helmholtz problems with absorption
Ivan G. Graham, Euan A. Spence, Eero Vainikko
In this paper we give new results on domain decomposition preconditioners for GMRES when computing piecewise-linear finite-element approximations of the Helmholtz equation $-Δu - (…
Petascale elliptic solvers for anisotropic PDEs on GPU clusters
Eike Hermann Müller, Robert Scheichl, Eero Vainikko
Memory bound applications such as solvers for large sparse systems of equations remain a challenge for GPUs. Fast solvers should be based on numerically efficient algorithms and im…