3 papers
cs.LG2026
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…
math.NA2016
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…
math.NA2015
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 - (…