6 citations · 10 across the 4 of their papers we have counts for
4 papers
Uncertainty Quantification in HSI Reconstruction using Physics-Aware Diffusion Priors and Optics-Encoded Measurements
Juan Romero, Qiang Fu, Matteo Ravasi +1
Hyperspectral image reconstruction from a compressed measurement is a highly ill-posed inverse problem. Current data-driven methods suffer from hallucination due to the lack of spe…
Plug-and-Play regularized 3D seismic inversion with 2D pre-trained denoisers
Nick Luiken, Juan Romero, Miguel Corrales +1
Post-stack seismic inversion is a widely used technique to retrieve high-resolution acoustic impedance models from migrated seismic data. Its modelling operator assumes that a migr…
IntraSeismic: a coordinate-based learning approach to seismic inversion
Juan Romero, Wolfgang Heidrich, Nick Luiken +1
Seismic imaging is the numerical process of creating a volumetric representation of the subsurface geological structures from elastic waves recorded at the surface of the Earth. As…
Posterior sampling with CNN-based, Plug-and-Play regularization with applications to Post-Stack Seismic Inversion
Muhammad Izzatullah, Tariq Alkhalifah, Juan Romero +3
Uncertainty quantification is crucial to inverse problems, as it could provide decision-makers with valuable information about the inversion results. For example, seismic inversion…