TU3.SC3.1
Deep Calibration and Operator Learning for Ground Penetrating Radar Imaging
Saurav K. Shastri, The Ohio State University, United States; Yanting Ma, Petros Boufounos, Hassan Mansour, Mitsubishi Electric Research Laboratories, United States
Session:
TU3.SC3: Learning methods for inverse problems Lecture
Track:
SiG-DML - Signal and Data Analytics for Machine Learning
Location:
Saint Clair 3
Presentation Time:
Tue, 27 Aug, 16:30 - 16:50 France Time (UTC +1)
Session Chair:
Laurent Jacques, UCLouvain
Presentation
Discussion
Resources
No resources available.
Session TU3.SC3
TU3.SC3.1: Deep Calibration and Operator Learning for Ground Penetrating Radar Imaging
Saurav K. Shastri, The Ohio State University, United States; Yanting Ma, Petros Boufounos, Hassan Mansour, Mitsubishi Electric Research Laboratories, United States
TU3.SC3.2: Whiteness-based bilevel learning of regularization parameters in imaging
Carlo Santambrogio, Science and High Technology Department, University of Insubria, Italy; Monica Pragliola, Dept. of Mathematics and Applications, University of Naples Federico II, Italy; Alessandro Lanza, Dept. of Mathematics, University of Bologna, Italy; Marco Donatelli, Science and High Technology Department, University of Insubria, Italy; Luca Calatroni, Laboratoire I3S, CNRS, UniCA, Inria, Sophia-Antipolis, France
TU3.SC3.3: RECOVERY GUARANTEES OF UNSUPERVISED NEURAL NETWORKS FOR INVERSE PROBLEMS TRAINED WITH GRADIENT DESCENT
Nathan Buskulic, Université de Caen, France; Jalal Fadili, ENSICAEN, France; Yvain Quéau, CNRS, France
TU3.SC3.4: RESTART STRATEGIES ENABLING AUTOMATIC DIFFERENTIATION FOR HYPERPARAMETER TUNING IN INVERSE PROBLEMS
Leo Davy, Nelly Pustelnik, Patrice Abry, Ecole Normale Supérieure de Lyon, France
TU3.SC3.5: Fast and Direct Angle Inference Using Masked Projection Modelling in 2D Tomography with Unknown Views
Jiakang Chen, Renke Wang, Vincent C. H. Leung, Pier Luigi Dragotti, Imperial College London, United Kingdom