@conference {herrmann2019NIPSliwcuc, title = {Learned imaging with constraints and uncertainty quantification}, booktitle = {Neural Information Processing Systems (NeurIPS)}, year = {2019}, note = {(NIPS, Vancouver)}, month = {12}, abstract = {We outline new approaches to incorporate ideas from convolutional networks into wave-based least-squares imaging. The aim is to combine hand-crafted constraints with deep convolutional networks allowing us to directly train a network capable of generating samples from the posterior. The main contributions include combination of weak deep priors with hard handcrafted constraints and a possible new way to sample the posterior.}, keywords = {constraint, deep learning, Imaging, Uncertainty quantification}, url = {https://slim.gatech.edu/Publications/Public/Conferences/NIPS/2019/herrmann2019NIPSliwcuc/herrmann2019NIPSliwcuc.html}, presentation = {https://slim.gatech.edu/Publications/Public/Conferences/NIPS/2019/herrmann2019NIPSliwcuc/herrmann2019NIPSliwcuc_pres.pdf}, url2 = {https://openreview.net/pdf?id=Hyet2Q29IS}, author = {Felix J. Herrmann and Ali Siahkoohi and Gabrio Rizzuti} }