An algebraic cubature formula on curvilinear polygons. - Gabriele Santin; Alvise Sommariva; Marco Vianello (Appl. Math. Comput., 2011)

A new stable basis for radial basis function interpolation. - Stefano De Marchi; Gabriele Santin (J. Comput. Appl. Math., 2013)

Approximation of eigenfunctions in kernel-based spaces. - Gabriele Santin; Robert Schaback (Adv. Comput. Math., 2016)

Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario. - Markus Köppel; Fabian Franzelin; Ilja Kröker; Sergey Oladyshkin; Gabriele Santin; Dominik Wittwar; Andrea Barth; Bernard Haasdonk; Wolfgang Nowak; Dirk Pflüger; Christian Rohde (CoRR, 2018)

Numerical modelling of a peripheral arterial stenosis using dimensionally reduced models and machine learning techniques. - Tobias Köppl; Gabriele Santin; Bernard Haasdonk; Rainer Helmig (CoRR, 2018)

Biomechanical Surrogate Modelling Using Stabilized Vectorial Greedy Kernel Methods. - Bernard Haasdonk; Tizian Wenzel; Gabriele Santin; Syn Schmitt (ENUMATH, 2019)

Kernel Methods for Surrogate Modeling. - Gabriele Santin; Bernard Haasdonk (CoRR, 2019)

A novel class of stabilized greedy kernel approximation algorithms: Convergence, stability & uniform point distribution. - Tizian Wenzel; Gabriele Santin; Bernard Haasdonk (CoRR, 2019)

Sampling based approximation of linear functionals in Reproducing Kernel Hilbert Spaces. - Gabriele Santin; Toni Karvonen; Bernard Haasdonk (CoRR, 2020)

Kernel methods for center manifold approximation and a data-based version of the Center Manifold Theorem. - Bernard Haasdonk; Boumediene Hamzi; Gabriele Santin; Dominik Wittwar (CoRR, 2020)

Structured Deep Kernel Networks for Data-Driven Closure Terms of Turbulent Flows. - Tizian Wenzel; Marius Kurz; Andrea Beck; Gabriele Santin; Bernard Haasdonk (LSSC, 2021)

Universality and Optimality of Structured Deep Kernel Networks. - Tizian Wenzel; Gabriele Santin; Bernard Haasdonk (CoRR, 2021)

Analysis of target data-dependent greedy kernel algorithms: Convergence rates for f-, $f cdot P$- and f/P-greedy. - Tizian Wenzel; Gabriele Santin; Bernard Haasdonk (CoRR, 2021)

Measuring close proximity interactions in summer camps during the COVID-19 pandemic. - Elia Leoni; Giulia Cencetti; Gabriele Santin; Timofei Istomin; Davide Molteni; Gian Pietro Picco; Elisabetta Farella; Bruno Lepri; A. M. Murphy (CoRR, 2021)

Convergence analysis for image interpolation in terms of the cSSIM. - Francesco Marchetti; Gabriele Santin (CoRR, 2021)

Greedy algorithms for learning via exponential-polynomial splines. - Rosanna Campagna; Stefano De Marchi; Emma Perracchione; Gabriele Santin (CoRR, 2021)

A novel class of stabilized greedy kernel approximation algorithms: Convergence, stability and uniform point distribution. - Tizian Wenzel; Gabriele Santin; Bernard Haasdonk (J. Approx. Theory, 2021)

A Framework for Verifiable and Auditable Collaborative Anomaly Detection. - Gabriele Santin; Inna Skarbovsky; Fabiana Fournier; Bruno Lepri (IEEE Access, 2022)

Stable interpolation with exponential-polynomial splines and node selection via greedy algorithms. - Rosanna Campagna; Stefano De Marchi; Emma Perracchione; Gabriele Santin (Adv. Comput. Math., 2022)

Reprogramming FairGANs with Variational Auto-Encoders: A New Transfer Learning Model. - Beatrice Nobile; Gabriele Santin; Bruno Lepri; Pierpaolo Brutti (CoRR, 2022)

A Framework for Verifiable and Auditable Federated Anomaly Detection. - Gabriele Santin; Inna Skarbovsky; Fabiana Fournier; Bruno Lepri (CoRR, 2022)

Stability of convergence rates: Kernel interpolation on non-Lipschitz domains. - Tizian Wenzel; Gabriele Santin; Bernard Haasdonk (CoRR, 2022)

Adaptive meshfree solution of linear partial differential equations with PDE-greedy kernel methods. - Tizian Wenzel; Daniel Winkle; Gabriele Santin; Bernard Haasdonk (CoRR, 2022)

Interpolation with the polynomial kernels. - Giacomo Elefante; Wolfgang Erb; Francesco Marchetti; Emma Perracchione; Davide Poggiali; Gabriele Santin (CoRR, 2022)

Measuring close proximity interactions in summer camps during the COVID-19 pandemic. - Elia Leoni; Giulia Cencetti; Gabriele Santin; Timofei Istomin; Davide Molteni; Gian Pietro Picco; Elisabetta Farella; Bruno Lepri; Amy L. Murphy (EPJ Data Sci., 2022)

Convergence Results in Image Interpolation With the Continuous SSIM. - Francesco Marchetti; Gabriele Santin (SIAM J. Imaging Sci., 2022)

Equally spaced points are optimal for Brownian Bridge kernel interpolation. - Gabriele Santin (Appl. Math. Lett., 2023)

Quantitative and Qualitative Evaluation of Reinforcement Learning Policies for Autonomous Vehicles. - Laura Ferrarotti; Massimiliano Luca; Gabriele Santin; Giorgio Previati; Gianpiero Mastinu; Elena Campi; Lorenzo Uccello; Antonino Albanese; Praveen Zalaya; Alessandro Roccasalva; Bruno Lepri (CoRR, 2023)

Kernel-based models for influence maximization on graphs based on Gaussian process variance minimization. - Salvatore Cuomo; Wolfgang Erb; Gabriele Santin (J. Comput. Appl. Math., 2023)

Graph Neural Networks for Temporal Graphs: State of the Art, Open Challenges, and Opportunities. - Antonio Longa; Veronica Lachi; Gabriele Santin; Monica Bianchini; Bruno Lepri; Pietro Lio; Franco Scarselli; Andrea Passerini (Trans. Mach. Learn. Res., 2023)

HJB-RBF Based Approach for the Control of PDEs. - Alessandro Alla; Hugo Oliveira; Gabriele Santin (J. Sci. Comput., 2023)

A Characterization Theorem for Equivariant Networks with Point-wise Activations. - Marco Pacini; Xiaowen Dong 001; Bruno Lepri; Gabriele Santin (ICLR, 2024)

Autonomous and Human-Driven Vehicles Interacting in a Roundabout: A Quantitative and Qualitative Evaluation. - Laura Ferrarotti; Massimiliano Luca; Gabriele Santin; Giorgio Previati; Gianpiero Mastinu; Massimiliano Gobbi; Elena Campi; Lorenzo Uccello; Antonino Albanese; Praveen Zalaya; Alessandro Roccasalva; Bruno Lepri (IEEE Access, 2024)

Kernel Methods for the Approximation of the Eigenfunctions of the Koopman Operator. - Jonghyeon Lee; Boumediene Hamzi; Boya Hou; Houman Owhadi; Gabriele Santin; Umesh Vaidya (CoRR, 2024)

On the Optimality of Target-Data-Dependent Kernel Greedy Interpolation in Sobolev Reproducing Kernel Hilbert Spaces. - Gabriele Santin; Tizian Wenzel; Bernard Haasdonk (SIAM J. Numer. Anal., 2024)

Separation Power of Equivariant Neural Networks. - Marco Pacini; Xiaowen Dong 001; Bruno Lepri; Gabriele Santin (ICLR, 2025)

An algorithm for a constrained P-spline. - Rosanna Campagna; Serena Crisci; Gabriele Santin; Gerardo Toraldo; Marco Viola (CoRR, 2025)

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; Francesco Marchetti (CoRR, 2025)

General superconvergence for kernel-based approximation. - Toni Karvonen; Gabriele Santin; Tizian Wenzel (CoRR, 2025)

Explaining the Explainers in Graph Neural Networks: a Comparative Study. - Antonio Longa; Steve Azzolin; Gabriele Santin; Giulia Cencetti; Pietro Lio; Bruno Lepri; Andrea Passerini (ACM Comput. Surv., 2025)

On Universality Classes of Equivariant Networks. - Marco Pacini; Gabriele Santin; Bruno Lepri; Shubhendu Trivedi (CoRR, 2025)

Kernel-based Greedy Approximation of Parametric Elliptic Boundary Value Problems. - Bernard Haasdonk; Gabriele Santin; Tizian Wenzel (CoRR, 2025)