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cs.LG2026
Bayesian Scattering: A Principled Baseline for Uncertainty on Image Data
Bernardo Fichera, Zarko Ivkovic, Kjell Jorner +2
Uncertainty quantification for image data is dominated by complex deep learning methods, yet the field lacks an interpretable, mathematically grounded baseline. We propose Bayesian…
cs.LG2022★ 3 cited
Linearization and Identification of Multiple-Attractor Dynamical Systems through Laplacian Eigenmaps
Bernardo Fichera, Aude Billard
Dynamical Systems (DS) are fundamental to the modeling and understanding time evolving phenomena, and have application in physics, biology and control. As determining an analytical…