3 papers
math.NA2025
General superconvergence for kernel-based approximation
Toni Karvonen, Gabriele Santin, Tizian Wenzel
Kernel interpolation is a fundamental technique for approximating functions from scattered data, with a well-understood convergence theory when interpolating elements of a reproduc…
math.NA2025
Tuning Butterworth filter's parameters in SPECT reconstructions via kernel-based Bayesian optimization with a no-reference image evaluation metric
Luca Pastrello, Diego Cecchin, Gabriele Santin +1
In Single Photon Emission Computed Tomography (SPECT), the image reconstruction process involves many tunable parameters that have a significant impact on the quality of the result…
cs.LG2024
A Characterization Theorem for Equivariant Networks with Point-wise Activations
Marco Pacini, Xiaowen Dong, Bruno Lepri +1
Equivariant neural networks have shown improved performance, expressiveness and sample complexity on symmetrical domains. But for some specific symmetries, representations, and cho…