Publications

• Tolulope Olugboji, Ziqi Zhang, Steve Carr, Canberk Ekmekci, and Mujdat Cetin, “On the Detection of Upper Mantle Discontinuities with Radon-Transformed Ps Receiver Functions (CRISP-RF)”, in Geophysical Journal International, 2023. [pdf]

• Canberk Ekmekci and Mujdat Cetin, “Quantifying Generative Model Uncertainty in Posterior Sampling Methods for Computational Imaging,” in NeurIPS 2023 Workshop on Deep Learning and Inverse Problems, 2023. [pdf]

• Canberk Ekmekci and Mujdat Cetin, “Automatic parameter tuning for Plug-and-Play algorithms using generalized cross validation and Stein’s unbiased risk estimation for linear inverse problems in computational imaging,” in IS&T International Symposium on Electronic Imaging, 2023. [pdf]

• Canberk Ekmekci and Mujdat Cetin, “Uncertainty Quantification for Deep Unrolling-Based Computational Imaging,” in IEEE Transactions on Computational Imaging, vol. 8, pp. 1195-1209, 2022, doi: 10.1109/TCI.2022.3233185. [pdf]

• Canberk Ekmekci and Mujdat Cetin, “What Does Your Computational Imaging Algorithm Not Know?: A Plug-and-Play Model Quantifying Model Uncertainty,” in IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2021. [pdf]

• Canberk Ekmekci and Mujdat Cetin, “Model-Based Bayesian Deep Learning Architecture for Linear Inverse Problems in Computational Imaging,” in IS&T International Symposium on Electronic Imaging, 2021. [pdf]