@conference {rizzuti2019EAGElis,
	title = {Learned iterative solvers for the Helmholtz equation},
	booktitle = {EAGE Annual Conference Proceedings},
	year = {2019},
	note = {(EAGE, Copenhagen)},
	month = {06},
	abstract = {We propose a {\textquoteleft}learned{\textquoteright} iterative solver for the Helmholtz equation, by combining traditional Krylov-based solvers with machine learning. The method is, in principle, able to circumvent the shortcomings of classical iterative solvers, and has clear advantages over purely data-driven ap- proaches. We demonstrate the effectiveness of this approach under a 1.5-D assumption, when ade- quate a priori information about the velocity distribution is known.},
	keywords = {EAGE, Helmholtz, Iterative, machine learning},
	doi = {10.3997/2214-4609.201901542},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2019/rizzuti2019EAGElis/rizzuti2019EAGElis.pdf},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2019/rizzuti2019EAGElis/rizzuti2019EAGElis_pres.pdf},
	author = {Gabrio Rizzuti and Ali Siahkoohi and Felix J. Herrmann}
}
