Gabriele Santin

Orcid: 0000-0001-6959-1070

According to our database1, Gabriele Santin authored at least 34 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A Characterization Theorem for Equivariant Networks with Point-wise Activations.
CoRR, 2024

2023
HJB-RBF Based Approach for the Control of PDEs.
J. Sci. Comput., July, 2023

Kernel-based models for influence maximization on graphs based on Gaussian process variance minimization.
J. Comput. Appl. Math., 2023

Quantitative and Qualitative Evaluation of Reinforcement Learning Policies for Autonomous Vehicles.
CoRR, 2023

On the optimality of target-data-dependent kernel greedy interpolation in Sobolev Reproducing Kernel Hilbert Spaces.
CoRR, 2023

Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities.
CoRR, 2023

Equally spaced points are optimal for Brownian Bridge kernel interpolation.
Appl. Math. Lett., 2023

2022
Convergence Results in Image Interpolation With the Continuous SSIM.
SIAM J. Imaging Sci., December, 2022

Measuring close proximity interactions in summer camps during the COVID-19 pandemic.
EPJ Data Sci., 2022

Interpolation with the polynomial kernels.
CoRR, 2022

Explaining the Explainers in Graph Neural Networks: a Comparative Study.
CoRR, 2022

Adaptive meshfree solution of linear partial differential equations with PDE-greedy kernel methods.
CoRR, 2022

Stability of convergence rates: Kernel interpolation on non-Lipschitz domains.
CoRR, 2022

A Framework for Verifiable and Auditable Federated Anomaly Detection.
CoRR, 2022

Reprogramming FairGANs with Variational Auto-Encoders: A New Transfer Learning Model.
CoRR, 2022

Stable interpolation with exponential-polynomial splines and node selection via greedy algorithms.
Adv. Comput. Math., 2022

A Framework for Verifiable and Auditable Collaborative Anomaly Detection.
IEEE Access, 2022

2021
A novel class of stabilized greedy kernel approximation algorithms: Convergence, stability and uniform point distribution.
J. Approx. Theory, 2021

Greedy algorithms for learning via exponential-polynomial splines.
CoRR, 2021

Convergence analysis for image interpolation in terms of the cSSIM.
CoRR, 2021

Measuring close proximity interactions in summer camps during the COVID-19 pandemic.
CoRR, 2021

Analysis of target data-dependent greedy kernel algorithms: Convergence rates for f-, $f \cdot P$- and f/P-greedy.
CoRR, 2021

Universality and Optimality of Structured Deep Kernel Networks.
CoRR, 2021

Structured Deep Kernel Networks for Data-Driven Closure Terms of Turbulent Flows.
Proceedings of the Large-Scale Scientific Computing - 13th International Conference, 2021

2020
Kernel methods for center manifold approximation and a data-based version of the Center Manifold Theorem.
CoRR, 2020

Sampling based approximation of linear functionals in Reproducing Kernel Hilbert Spaces.
CoRR, 2020

2019
A novel class of stabilized greedy kernel approximation algorithms: Convergence, stability & uniform point distribution.
CoRR, 2019

Kernel Methods for Surrogate Modeling.
CoRR, 2019

Biomechanical Surrogate Modelling Using Stabilized Vectorial Greedy Kernel Methods.
Proceedings of the Numerical Mathematics and Advanced Applications ENUMATH 2019 - European Conference, Egmond aan Zee, The Netherlands, September 30, 2019

2018
Numerical modelling of a peripheral arterial stenosis using dimensionally reduced models and machine learning techniques.
CoRR, 2018

Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario.
CoRR, 2018

2016
Approximation of eigenfunctions in kernel-based spaces.
Adv. Comput. Math., 2016

2013
A new stable basis for radial basis function interpolation.
J. Comput. Appl. Math., 2013

2011
An algebraic cubature formula on curvilinear polygons.
Appl. Math. Comput., 2011


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