Emma Perracchione

Orcid: 0000-0003-2663-7803

According to our database1, Emma Perracchione authored at least 35 papers between 2015 and 2024.

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

Timeline

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Bibliography

2024
Classifier-dependent feature selection via greedy methods.
Stat. Comput., October, 2024

Data-Driven Kernel Designs for Optimized Greedy Schemes: A Machine Learning Perspective.
SIAM J. Sci. Comput., February, 2024

A recipe based on Lebesgue functions for learning Variably Scaled Kernels via Discontinuous Neural Networks (ΔNN-VSKs).
CoRR, 2024

RIS: Regularized Imaging Spectroscopy for STIX on-board Solar Orbiter.
CoRR, 2024

Forecasting Geoffective Events from Solar Wind Data and Evaluating the Most Predictive Features through Machine Learning Approaches.
CoRR, 2024

Greedy feature selection: Classifier-dependent feature selection via greedy methods.
CoRR, 2024

AI-FLARES: Artificial Intelligence for the Analysis of Solar Flares Data.
CoRR, 2024

2023
Learning with Partition of Unity-based Kriging Estimators.
Appl. Math. Comput., July, 2023

Unbiased CLEAN for STIX in Solar Orbiter.
CoRR, 2023

Mapped Variably Scaled Kernels: Applications to Solar Imaging.
Proceedings of the Computational Science and Its Applications - ICCSA 2023 Workshops, 2023

2022
Local-to-Global Support Vector Machines (LGSVMs).
Pattern Recognit., 2022

Efficient Reduced Basis Algorithm (ERBA) for Kernel-Based Approximation.
J. Sci. Comput., 2022

Interpolation with the polynomial kernels.
CoRR, 2022

Forward-fitting STIX visibilities.
CoRR, 2022

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

2021
Data-Driven Extrapolation Via Feature Augmentation Based on Variably Scaled Thin Plate Splines.
J. Sci. Comput., 2021

A greedy non-intrusive reduced order model for shallow water equations.
J. Comput. Phys., 2021

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

Imaging from STIX visibility amplitudes.
CoRR, 2021

Data-driven reduced order modeling of environmental hydrodynamics using deep autoencoders and neural ODEs.
CoRR, 2021

Feature augmentation for the inversion of the Fourier transform with limited data.
CoRR, 2021

Multivariate approximation at fake nodes.
Appl. Math. Comput., 2021

Learning via variably scaled kernels.
Adv. Comput. Math., 2021

2020
Shape-Driven Interpolation With Discontinuous Kernels: Error Analysis, Edge Extraction, and Applications in Magnetic Particle Imaging.
SIAM J. Sci. Comput., 2020

Polynomial interpolation via mapped bases without resampling.
J. Comput. Appl. Math., 2020

Developing food, water and energy nexus workflows.
Int. J. Digit. Earth, 2020

Visibility Interpolation in Solar Hard X-ray Imaging: Application to RHESSI and STIX.
CoRR, 2020

2019
RBF-Based Partition of Unity Methods for Elliptic PDEs: Adaptivity and Stability Issues Via Variably Scaled Kernels.
J. Sci. Comput., 2019

Fast and stable rational RBF-based partition of unity interpolation.
J. Comput. Appl. Math., 2019

2018
Optimal Selection of Local Approximants in RBF-PU Interpolation.
J. Sci. Comput., 2018

2017
Positive constrained approximation via RBF-based partition of unity method.
J. Comput. Appl. Math., 2017

2016
Robust Approximation Algorithms for the Detection of Attraction Basins in Dynamical Systems.
J. Sci. Comput., 2016

Efficient computation of partition of unity interpolants through a block-based searching technique.
Comput. Math. Appl., 2016

2015
Partition of unity interpolation on multivariate convex domains.
Int. J. Model. Simul. Sci. Comput., 2015

Reliable approximation of separatrix manifolds in competition models with safety niches.
Int. J. Comput. Math., 2015


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