E. Perracchione, M. Polato, W. Erb, F. Piazzon, F. Marchetti, F. Aiolli, B. Bayat, A. Botto, S. De Marchi, S. Kollet, C. Montzka, A. Sperduti, M. Vianello, M. Putti, Modelling and processing services and tools, 2019, GEO Essential Deliverable 1.3.
E. Perracchione, M. Polato, W. Erb, F. Piazzon, F. Marchetti, F. Aiolli, B. Bayat, A. Botto, S. De Marchi, S. Kollet, C. Montzka, A. Sperduti, M. Vianello, M. Putti, Data fusion guidelines, 2019, GEO Essential Deliverable 1.6.
G. Audone, F. Della Santa, E. Perracchione, S. Pieraccini, A recipe for learning Variably Scaled Kernels via Discontinuous Neural Networks, J. Comput. Appl. Math. , vol. 469, 1-18.
A. Volpara, A. Lupoli, F. Filbir, E. Perracchione, A.M. Massone, M. Piana, RIS: Regularized imaging spectroscopy for STIX on board Solar Orbiter, A&A, A47, 2025.
T. Wenzel, F. Marchetti, E. Perracchione, Data-Driven Kernel Designs for Optimized Greedy Schemes: A Machine Learning Perspective, SIAM J. Sci. Comput. 46, C101-C126, 2024.
F. Camattari, S. Guastavino, F. Marchetti, M. Piana, E. Perracchione, Classifier-dependent feature selection via greedy methods, Statistics and Computing, 2024, 34(5), 151.
S. Guastavino, K. Bahamazava, E. Perracchione, F. Camattari, G. Audone, D. Telloni, R. Susino, G. Nicolini, S. Fineschi, M. Piana, Forecasting Geoffective Events from Solar Wind Data and Evaluating the Most Predictive Features through Machine Learning Approaches, The Astrophys. J., 94, 2024.
H. Muller, P. Massa, A. Mus, J.S. Kim, E. Perracchione, Identifying synergies between VLBI and STIX imaging, Astronom. Astrophys. 84, 2024, A47.
E. Perracchione, F. Camattari, A. Volpara, P. Massa, A.M. Massone, M. Piana, Unbiased CLEAN for STIX in Solar Orbiter, The Astrophys. J. Suppl. Series 268, 2023.
P. Massa, G. J. Hurford, A. Volpara, M. Kuhar, A.F. Battaglia, H. Xiao, D. Casadei, E. Perracchione, S. Garbarino, S. Guastavino, H. Collier, E.C.M. Dickson, A. Gordon Emslie, D.F. Ryan, S.A. Maloney, F. Schuller, A. Warmuth, A.M. Massone, F. Benvenuto, M. Piana, S. Krucker, The STIX Imaging Concept, Sol Phys. 114, 2023.
A. Volpara, P. Massa, E. Perracchione, M. Piana, A.M. Massone, Forward fitting STIX visibilities, Astronom. Astrophys. 668, 2022, A145.
F. Marchetti, E. Perracchione, Local-to-Global Support Vector Machines (LGSVMs), Pattern Recognit. 132, 2022, 108920.
R. Cavoretto, A. De Rossi, E. Perracchione, Learning with Partition of Unity-based Kriging Estimators, Appl. Math. Comput. 448, 2023, 127938.
G. Elefante, W. Erb, F. Marchetti, E. Perracchione, D. Poggiali, G. Santin, Interpolation with the polynomial kernels, Dolomites Res. Notes Approx. 15, 2022, 45–60.
P. Massa, A.F. Battaglia, A. Volpara, H. Collier, G.J. Hurford, M. Kuhar, E. Perracchione, Emma S. Garbarino, A.M. Massone, F. Benvenuto, F. Schuller, A. Warmuth, E.C.M. Dickson, H. Xiao, S.A. Maloney, D.F. Ryan, M. Piana, S. Krucker, First Hard X-Ray Imaging Results by Solar Orbiter STIX, Sol. Phys. 297, 2022, 93.
R. Cavoretto, A. De Rossi, S. Lancellotti, E. Perracchione, Software Implementation of the Partition of Unity Method, Dolomites Res. Notes Approx. 15, 2022, 35–46
F. Marchetti, E. Perracchione, Efficient Reduced Basis Algorithm (ERBA) for Kernel-Based Approximation, J. Sci. Comput. 91, 2022, 41
E. Perracchione, A.M. Massone, M. Piana, Feature augmentation for the inversion of the Fourier transform with limited data, Inverse Probl., 37, 2021, 105001.
P. Massa, E. Perracchione, Garbarino S., A.F. Battaglia, F. Benvenuto, M. Piana, G. Hurford, S. Krucker, Imaging from STIX visibility amplitudes, Astron. Astrophys. 656, 2021, A25.
A. Battaglia, J. Saqri, P. Massa, E. Perracchione, E. Dickson, H. Xiao, A. Veronig, A. Warmuth, M. Battaglia, G. Hurford, A. Meuris, O. Limousin, L. Etesi, S. Maloney, R. Schwartz, M. Kuhar, F. Schuller, V.S. Pavai, S. Musset, D. Ryan, L. Kleint, M. Piana, A. Massone, F. Benvenuto, J. Sylwester, M. Litwicka, M. Stkeslicki, T. Mrozek, N. Vilmer, F. Farnik, J. Kavsparova, G. Mann, P. Gallagher, B. Dennis, A. Csillaghy, A. Benz, S. Krucker, STIX X-ray microflare observations during the Solar Orbiter commissioning phase, Astron. Astrophys. 656 (2021), A4.
E. Perracchione, P. Massa, A.M. Massone, M. Piana, Visibility Interpolation in Solar Hard X-ray Imaging: Application to RHESSI and STIX, 2021, 919 (2021), 133.
C. Campi, F. Marchetti, Perracchione, Learning via variably scaled kernels, Adv. Comput. Math. 47 (2021), 51.
R. Campagna, E. Perracchione, Data-Driven Extrapolation Via Feature Augmentation Based on Variably Scaled Thin Plate Splines, J. Sci. Comput. 88 (2021), 15.
S. Dutta, M.W. Farthing, E. Perracchione, G. Savant, M. Putti, A greedy non-intrusive reduced order model for shallow water equations, J. Comput. Phys. 439 (2021), 110378.
M. Azaïez, T. Chacón Rebollo, M.G. Marmól, E. Perracchione, A. Rincón Casado, J.M. Vega, Data-driven reduced order modeling based on tensor decompositions and its application to air-wall heat transfer in buildings, SeMA Journal, 78 (2021), 213– 232.
S. De Marchi, G. Elefante, E. Perracchione, D. Poggiali, Quadrature at fake nodes, Dolomites Res. Notes Approx., 14 (2021), 39–45.
S. De Marchi, F. Marchetti, E. Perracchione, D. Poggiali, Multivariate approximation at fake nodes, Appl. Math. Comput. 319 (2021), 125628.
M. Buhmann, S. De Marchi, E. Perracchione, Analysis of a new class of rational RBF expansions, IMA J. Numer. Anal. 40 (2020), 1972–1993.
E. Perracchione, RBF-based tensor decomposition with applications to oenology, Dolomites Res. Notes Approx. 13 (2020), 36–46.
S. De Marchi, W. Erb, F. Marchetti, E. Perracchione, M. Rossini, Shape-Driven Interpolation with Discontinuous Kernels: Error Analysis, Edge Extraction and Applications in Magnetic Particle Imaging, SIAM J. Sci. Comput. 42 (2020), B472– B491.
S. De Marchi, F. Marchetti, E. Perracchione, Jumping with Variably Scaled Discontinuous kernels (VSDKs), BIT Numerical Mathematics, 60 (2020), 441–463.
S. De Marchi, F. Marchetti, E. Perracchione, D. Poggiali, Polynomial interpolation via mapped bases without resampling, J. Comput. Appl. Math. 364 (2020), 112347.
R. Campagna, S. Cuomo, S. De Marchi, E. Perracchione, G. Severino, A stable meshfree PDE solver for source-type flows in porous media, Appl. Num. Math. 149 (2020), 30–42.
I. McCallum, C. Montzka, B. Bayat, S. Kollet, A. Kolotii, N. Kussul, M. Lavreniuk, A. Lehmann, J. Maso, P. Mazzetti, A. Mosnier, E. Perracchione, M. Putti, M. Santoro, I. Serral, L. Shumilo, D. Spengler, S. Fritz, Developing food, water and energy nexus workflows, Int. J. Digit. Earth, 13 (2019), 299–308.
M. Aminian Shahrokhabadi, A. Neisy, E. Perracchione, M. Polato, Learning with subsampled kernel-based methods: Environmental and financial applications, Dolomites Res. Notes Approx. 12 (2019), 17–27.
S. De Marchi, A. Martínez, E. Perracchione, M. Rossini, RBF-based partition of unity methods for elliptic PDEs: Adaptivity and stability issues via variably scaled kernels, J. Sci. Comput. 79 (2019), 321-344.
S. De Marchi, A. Martínez, E. Perracchione, Fast and stable rational RBF-based partition of unity interpolation, J. Comput. Appl. Math. 349 (2019), 331–343.
M. Azaïez, T. Chácon Rebollo, E. Perracchione, J. M. Vega, Recursive POD expansion for advection-diffusion-reaction equation, Comm. Comput. Physics 24 (2018), 1556–1578.
E. Perracchione, Rational RBF-based partition of unity method for efficiently and accurately approximating 3D objects, Comput. Appl. Math. (2018), 37, 4633– 4648.
I. Stura, E. Perracchione, G. Migliaretti, F. Cavallo, A new numerical method for processing longitudinal data: clinical applications, Epidemiology Biostatistics and Public Health 15 (2018), 1–8.
R. Cavoretto, A. De Rossi, E. Perracchione, Optimal selection of local approximants in RBF-PU interpolation using bivariate LOOCV, J. Sci. Comput. 74 (2018), 1–22.
A. De Rossi, E. Perracchione, E. Venturino, Meshless partition of unity method for attraction basins of periodic orbits: Fast detection of separatrix points, Dolomites Res. Notes Approx. 11 (2018), 15–22.
A. De Rossi, E. Perracchione, Positive constrained approximation via RBF-based partition of unity method, J. Comput. Appl. Math. 319 (2017), 338–351.
R. Cavoretto, S. De Marchi, A. De Rossi, E. Perracchione, G. Santin, Partition of unity interpolation using stable kernel-based techniques, Appl. Numer. Math. 116 (2017), 95–107.
E. Perracchione, I. Stura, RBF kernel method and its applications to clinical data, Dolomites Res. Notes Approx. 9 (2016), 13–18.
A. De Rossi, E. Perracchione, E. Venturino, Fast strategy for PU interpolation: An application for the reconstruction of separatrix manifolds, Dolomites Res. Notes Approx. 9 (2016), 2–12.
R. Cavoretto, A. De Rossi, E. Perracchione, Efficient computation of partition of unity interpolants through a block-based searching technique, Comput. Math. Appl. 71 (2016), 2568–2584.
R. Cavoretto, A. De Rossi, E. Perracchione, E. Venturino, Graphical representation of separatrices of attraction basins in two and three dimensional dynamical systems, Int. J. Comput. Math. 14 (2017), . 1750008-1–1750008-16.
R. Cavoretto, A. De Rossi, E. Perracchione, E. Venturino, Robust approximation algorithms for the detection of attraction basins in dynamical systems, J. Sci. Comput. 68 (2016), 395–415.
R. Cavoretto, A. De Rossi, E. Perracchione, Partition of unity interpolation on multivariate convex domains, Int. J. Model. Simul. Sci. Comput. 6 (2015), 1–17.
R. Cavoretto, A. De Rossi, E. Perracchione, E. Venturino, Reliable approximation of separatrix manifolds in competition models with safety niches, Int. J. Comput. Math. 92 (2015), 1826–1837.
F Marchetti, E. Perracchione, A. Volpara, A.M. Massone, S. De Marchi, M. Piana, Mapped Variably Scaled Kernels: Applications to Solar Imaging, In: Gervasi, O., et al. Computational Science and Its Applications, ICCSA 2023. Lecture Notes in Computer Science, vol 14108. Springer, 2023.
R. Campagna, E. Perracchione, Feature Augmentation for Numerical Inversion of Multi-exponential Decay Curves, AIP Conference Proceedings, 2022, 050004.
S. De Marchi, W. Erb, E. Francomano, F. Marchetti, E. Perracchione, D. Poggiali, Fake nodes approximation for magnetic particle imaging, in: 20th IEEE Mediterranean Electrotechnical Conference, MELECON 2020 – Proceedings, 2020, 434– 438.
R. Cavoretto, A. De Rossi, G. E. Fasshauer, M. J. McCourt, E. Perracchione, Anisotropic weights for RBF-PU interpolation with subdomains of variable shapes, in: F.A. Radu at al. (Eds.), Proc. of ENUMATH17, 2019, Lecture Notes in Computational Science and Engineering 126, 93-101.
R. Cavoretto, A. De Rossi, E. Perracchione, Surface approximation of basins of attraction through RBF interpolation schemes, in: J. Vigo-Aguiar et al. (Eds.), Proc. of CMMSE17, vol. 2, 2017, 523–529.
R. Cavoretto, A. De Rossi, E. Perracchione, RBF-PU interpolation with variable subdomain sizes and shape parameters, in: T.E. Simos et al. (Eds.), NUMPTA16 AIP Conf. Proc., vol. 1776, 2016, 070003-1–070003-4.
R. Cavoretto, S. De Marchi, A. De Rossi, E. Perracchione, G. Santin, Approximating basins of attraction for dynamical systems via stable radial bases, in: T.E. Simos et al. (Eds.), ICNAAM15 AIP Conf. Proc., vol. 1738, 2016, 390003-1–390003-4.
E. Perracchione, I. Stura, A RBF-PSO based approach for modeling prostate cancer, in: T.E. Simos et al. (Eds.), ICNAAM15 AIP Conf. Proc., vol. 1738, 2016, 390008-1–390008-4.
R. Cavoretto, A. De Rossi, E. Perracchione, Fast and flexible interpolation via PUM with applications in population dynamics, in: T.E. Simos et al. (Eds.), ICNAAM15 AIP Conf. Proc., vol. 1738, 2016, 390005-1–390005-4.
R. Cavoretto, S. De Marchi, A. De Rossi, E. Perracchione and G. Santin, RBF approximation of large datasets by partition of unity and local stabilization, in: I.P. Hamilton et al. (Eds.), Proc. of CMMSE15, 2015, 317–326.
G. Sabetta, E. Perracchione, E. Venturino, Wild herbivores in forests: four case studies, in: R.P. Mondaini (Ed.), Proc. of BIOMAT14, 2015, 56–77.
A. De Rossi, I. Ferrua, E. Perracchione, G. Ruatta, E. Venturino, Competition models with niche for squirrel population dynamics, in: T.E. Simos et al. (Eds.), ICNAAM13 AIP Conf. Proc., vol. 1558, 2013, 1818–1821.
R. Cavoretto, A. De Rossi, E. Perracchione, E. Venturino, Reconstruction of separatrix curves and surfaces in squirrels competition models with niche, in: I.P. Hamilton et al. (Eds.), Proc. of CMMSE13, vol. 2, 2013, 400–411.