A logical exposition of dirac 3-polarizer experiment and its potential impact on computational biology. - Wen-Ran Zhang; Francesco Marchetti (BCB, 2015)

Intelligent Control: A Taxonomy. - Callum Wilson; Francesco Marchetti; Marilena Di Carlo; Annalisa Riccardi; Edmondo A. Minisci (ICSC, 2019)

A Hybrid Neural Network-Genetic Programming Intelligent Control Approach. - Francesco Marchetti; Edmondo A. Minisci (BIOMA, 2020)

MANTRA: Memory Augmented Networks for Multiple Trajectory Prediction. - Francesco Marchetti; Federico Becattini; Lorenzo Seidenari; Alberto Del Bimbo (CVPR, 2020)

Variably Scaled Kernels Improve Classification of Hormonally-Treated Patient-Derived Xenografts. - Francesco Marchetti; Fabio De Martino; Marie Shamseddin; Stefano De Marchi; Cathrin Brisken (EAIS, 2020)

Towards Intelligent Control via Genetic Programming. - Francesco Marchetti; Edmondo A. Minisci; Annalisa Riccardi (IJCNN, 2020)

Treating the Gibbs phenomenon in barycentric rational interpolation and approximation via the S-Gibbs algorithm. - Jean-Paul Berrut; Stefano De Marchi; Giacomo Elefante; Francesco Marchetti (Appl. Math. Lett., 2020)

Polynomial interpolation via mapped bases without resampling. - Stefano De Marchi; Francesco Marchetti; Emma Perracchione; Davide Poggiali (J. Comput. Appl. Math., 2020)

Classifying Intelligence in Machines: A Taxonomy of Intelligent Control. - Callum Wilson; Francesco Marchetti; Marilena Di Carlo; Annalisa Riccardi; Edmondo A. Minisci (Robotics, 2020)

Shape-Driven Interpolation With Discontinuous Kernels: Error Analysis, Edge Extraction, and Applications in Magnetic Particle Imaging. - Stefano De Marchi; Wolfgang Erb; Francesco Marchetti; Emma Perracchione; M. Rossini (SIAM J. Sci. Comput., 2020)

Inclusive Genetic Programming. - Francesco Marchetti; Edmondo A. Minisci (EuroGP, 2021)

Convolutional Generative Adversarial Network, via Transfer Learning, for Traditional Scottish Music Generation. - Francesco Marchetti; Callum Wilson; Cheyenne Powell; Edmondo A. Minisci; Annalisa Riccardi (EvoMUSART, 2021)

Learning via variably scaled kernels. - Cristina Campi; Francesco Marchetti; Emma Perracchione (Adv. Comput. Math., 2021)

Multivariate approximation at fake nodes. - Stefano De Marchi; Francesco Marchetti; Emma Perracchione; Davide Poggiali (Appl. Math. Comput., 2021)

The extension of Rippa's algorithm beyond LOOCV. - Francesco Marchetti (Appl. Math. Lett., 2021)

Stable discontinuous mapped bases: the Gibbs-Runge-Avoiding Stable Polynomial Approximation (GRASPA) method. - Stefano De Marchi; Giacomo Elefante; Francesco Marchetti (Comput. Appl. Math., 2021)

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

On Kosloff Tal-Ezer least-squares quadrature formulas. - Giacomo Cappellazzo; Wolfgang Erb; Francesco Marchetti; Davide Poggiali (CoRR, 2021)

Implementation paradigm for supervised flare forecasting studies: a deep learning application with video data. - Sabrina Guastavino; Francesco Marchetti; Federico Benvenuto; Cristina Campi; Michele Piana (CoRR, 2021)

On (β, γ)-Chebyshev functions and points of the interval. - Stefano De Marchi; Giacomo Elefante; Francesco Marchetti (J. Approx. Theory, 2021)

Explainable Sparse Attention for Memory-Based Trajectory Predictors. - Francesco Marchetti; Federico Becattini; Lorenzo Seidenari; Alberto Del Bimbo (ECCV Workshops (5), 2022)

Deep variational learning for multiple trajectory prediction of 360° head movements. - Quentin Guimard; Lucile Sassatelli; Francesco Marchetti; Federico Becattini; Lorenzo Seidenari; Alberto Del Bimbo (MMSys, 2022)

A stochastic extended Rippa's algorithm for LpOCV. - Leevan Ling; Francesco Marchetti (Appl. Math. Lett., 2022)

Variably Scaled Persistence Kernels (VSPKs) for persistent homology applications. - Stefano De Marchi; Federico Lot; Francesco Marchetti; Davide Poggiali (CoRR, 2022)

Polynomial mapped bases: theory and applications. - Stefano De Marchi; Giacomo Elefante; Elisa Francomano; Francesco Marchetti (CoRR, 2022)

Operational solar flare forecasting via video-based deep learning. - Sabrina Guastavino; Francesco Marchetti; Federico Benvenuto; Cristina Campi; Michele Piana (CoRR, 2022)

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

Efficient Reduced Basis Algorithm (ERBA) for Kernel-Based Approximation. - Francesco Marchetti; Emma Perracchione (J. Sci. Comput., 2022)

Score-Oriented Loss (SOL) functions. - Francesco Marchetti; Sabrina Guastavino; Michele Piana; Cristina Campi (Pattern Recognit., 2022)

Local-to-Global Support Vector Machines (LGSVMs). - Francesco Marchetti; Emma Perracchione (Pattern Recognit., 2022)

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

Mapped Variably Scaled Kernels: Applications to Solar Imaging. - Francesco Marchetti; Emma Perracchione; Anna Volpara; Anna Maria Massone; Stefano De Marchi; Michele Piana (ICCSA (Workshops 5), 2023)

Moving Least Squares Approximation using Variably Scaled Discontinuous Weight Function. - Mohammad Karimnejad Esfahani; Stefano De Marchi; Francesco Marchetti (CoRR, 2023)

More properties of (β, γ)-Chebyshev functions and points. - Stefano De Marchi; Giacomo Elefante; Francesco Marchetti (CoRR, 2023)

Physics-driven machine learning for the prediction of coronal mass ejections' travel times. - Sabrina Guastavino; Valentina Candiani; Alessandro Bemporad; Francesco Marchetti; Federico Benvenuto; Anna Maria Massone; Roberto Susino; Daniele Telloni; Silvano Fineschi; Michele Piana (CoRR, 2023)

Robot Pose Nowcasting: Forecast the Future to Improve the Present. - Alessandro Simoni; Francesco Marchetti; Guido Borghi; Federico Becattini; Lorenzo Seidenari; Roberto Vezzani; Alberto Del Bimbo (CoRR, 2023)

Multiple Trajectory Prediction of Moving Agents With Memory Augmented Networks. - Francesco Marchetti; Federico Becattini; Lorenzo Seidenari; Alberto Del Bimbo (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Full Inclusive Genetic Programming. - Francesco Marchetti; Mauro Castelli; Illya Bakurov; Leonardo Vanneschi (CEC, 2024)

Depth-Based Privileged Information for Boosting 3D Human Pose Estimation on RGB. - Alessandro Simoni; Francesco Marchetti; Guido Borghi; Federico Becattini; Davide Davoli 002; Lorenzo Garattoni; Gianpiero Francesca; Lorenzo Seidenari; Roberto Vezzani (ECCV Workshops (13), 2024)

A fast surrogate cross validation algorithm for meshfree RBF collocation approaches. - Francesco Marchetti (Appl. Math. Comput., 2024)

Automatic design of interpretable control laws through parametrized Genetic Programming with adjoint state method gradient evaluation. - Francesco Marchetti; Gloria Pietropolli; Federico Julian Camerota Verdù; Mauro Castelli; Edmondo A. Minisci (Appl. Soft Comput., 2024)

AI-FLARES: Artificial Intelligence for the Analysis of Solar Flares Data. - Michele Piana; Federico Benvenuto; Anna Maria Massone; Cristina Campi; Sabrina Guastavino; Francesco Marchetti; Paolo Massa; Emma Perracchione; Anna Volpara (CoRR, 2024)

Greedy feature selection: Classifier-dependent feature selection via greedy methods. - Fabiana Camattari; Sabrina Guastavino; Francesco Marchetti; Michele Piana; Emma Perracchione (CoRR, 2024)

Data-Driven Kernel Designs for Optimized Greedy Schemes: A Machine Learning Perspective. - Tizian Wenzel; Francesco Marchetti; Emma Perracchione (SIAM J. Sci. Comput., 2024)

SMEMO: Social Memory for Trajectory Forecasting. - Francesco Marchetti; Federico Becattini; Lorenzo Seidenari; Alberto Del Bimbo (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Deep Variational Learning for 360° Adaptive Streaming. - Quentin Guimard; Lucile Sassatelli; Francesco Marchetti; Federico Becattini; Lorenzo Seidenari; Alberto Del Bimbo (ACM Trans. Multim. Comput. Commun. Appl., 2024)

Classifier-dependent feature selection via greedy methods. - Fabiana Camattari; Sabrina Guastavino; Francesco Marchetti; Michele Piana; Emma Perracchione (Stat. Comput., 2024)

3D Pose Nowcasting: Forecast the future to improve the present. - Alessandro Simoni; Francesco Marchetti; Guido Borghi; Federico Becattini; Lorenzo Seidenari; Roberto Vezzani; Alberto Del Bimbo (Comput. Vis. Image Underst., 2025)

A comprehensive theoretical framework for the optimization of neural networks classification performance with respect to weighted metrics. - Francesco Marchetti; Sabrina Guastavino; Cristina Campi; Federico Benvenuto; Michele Piana (Optim. Lett., 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)

Multiclass threshold-based classification. - Francesco Marchetti; Edoardo Legnaro; Sabrina Guastavino (CoRR, 2025)