Learning and Inverse Problems special issue to be published in Inverse Problems


Inverse Problems is pleased to announce the following upcoming 2016 special issue entitled ‘Learning and Inverse Problems’.

This special issue aims at bringing together articles that discuss recent advances on analyzing and optimizing inversion models. Several strategies for conceiving optimization problems, combining prior and data information, have been considered. Let us evoke statistically grounded methods, model design under uncertainties, parameter choice rules, adaptive regularization, dictionary learning, bilevel optimization, among others. Application areas include, but are not limited to, biomedical engineering and imaging, remote sensing and seismic imaging, astronomy, oceanography, atmospheric sciences and meteorology, chemical engineering and material sciences, computer vision and image processing. The guest editors are Juan Carlos De Los Reyes (MODEMAT, EPN Quito, Ecuador), Eldad Haber (University of British Columbia, Canada) and Carola-Bibiane Schönlieb (University of Cambridge, UK).


This special issue is now open for submissions. We also kindly ask you to distribute this call among all colleagues who might be interested in submitting their work.


All papers will be refereed to the usual high standard of Inverse Problems, and must fall within the journal’s scope, available at




We invite you to submit your manuscript via http://mc04.manuscriptcentral.com/ip-iop. Please make sure that you select “Special Issue Article” and “Special Issue on learning and inverse problems” from the drop-down menus on the submission page.


The closing date for submissions is 18 January 2016.