How to Handle Error Bars in Symbolic Regression for Data Mining in Scientific Applications. - Andrea Murari; Emmanuele Peluso; Michela Gelfusa; Michele Lungaroni; Pasqualino Gaudio (SLDS, 2015)

A Metric to Improve the Robustness of Conformal Predictors in the Presence of Error Bars. - Andrea Murari; Saeed Talebzadeh; Jesús Vega; Emmanuele Peluso; Michela Gelfusa; Michele Lungaroni; Pasqualino Gaudio (COPA, 2016)

Complex networks for the analysis of the synchronization of time series relevant for plasma fusion diagnostics. - Teddy Craciunescu; Andrea Murari; Emmanuele Peluso; Michela Gelfusa; Michele Lungaroni; Pasqualino Gaudio (ECCTD, 2017)

Deriving Realistic Mathematical Models from Support Vector Machines for Scientific Applications. - Andrea Murari; Emmanuele Peluso; Saeed Talebzadeh; Pasqualino Gaudio; Michele Lungaroni; Ondrej Mikulin; Jesús Vega; Michela Gelfusa (KDIR, 2017)

Detection of Causal Relations in Time Series Affected by Noise in Tokamaks Using Geodesic Distance on Gaussian Manifolds. - Andrea Murari; Teddy Craciunescu; Emmanuele Peluso; Michela Gelfusa; J. E. T. Contributors (Entropy, 2017)

A New Approach to Bolometric Tomography in Tokamaks. - Teddy Craciunescu; Andrea Murari; Emmanuele Peluso; Michela Gelfusa (ISCAS, 2018)

Improving Entropy Estimates of Complex Network Topology for the Characterization of Coupling in Dynamical Systems. - Teddy Craciunescu; Andrea Murari; Michela Gelfusa (Entropy, 2018)

On the Use of Transfer Entropy to Investigate the Time Horizon of Causal Influences between Signals. - Andrea Murari; Michele Lungaroni; Emmanuele Peluso; Pasquale Gaudio; Ernesto Lerche; Luca Garzotti; Michela Gelfusa; J. E. T. Contributors (Entropy, 2018)

Geodesic Distance on Gaussian Manifolds to Reduce the Statistical Errors in the Investigation of Complex Systems. - Michele Lungaroni; Andrea Murari; Emmanuele Peluso; Pasqualino Gaudio; Michela Gelfusa (Complex., 2019)

Causality Detection Methods Applied to the Investigation of Malaria Epidemics. - Teddy Craciunescu; Andrea Murari; Michela Gelfusa (Entropy, 2019)

Image-Based Methods to Investigate Synchronization between Time Series Relevant for Plasma Fusion Diagnostics. - Teddy Craciunescu; Andrea Murari; Ernesto Lerche; Michela Gelfusa; J. E. T. Contributors (Entropy, 2020)

Quantifying Total Influence between Variables with Information Theoretic and Machine Learning Techniques. - Andrea Murari; Riccardo Rossi; Michele Lungaroni; Pasquale Gaudio; Michela Gelfusa (Entropy, 2020)

Upgrading Model Selection Criteria with Goodness of Fit Tests for Practical Applications. - Riccardo Rossi; Andrea Murari; Pasquale Gaudio; Michela Gelfusa (Entropy, 2020)

Adaptive Quasi-Unsupervised Detection of Smoke Plume by LiDAR. - Riccardo Rossi; Michela Gelfusa; Andrea Malizia; Pasqualino Gaudio (Sensors, 2020)

The Reciprocal Influence Criterion: An Upgrade of the Information Quality Ratio. - Riccardo Rossi; Michela Gelfusa; Filippo De Masi; Matteo Ossidi; Andrea Murari (Complex., 2021)

Improved Treatment of the Independent Variables for the Deployment of Model Selection Criteria in the Analysis of Complex Systems. - Luca Spolladore; Michela Gelfusa; Riccardo Rossi; Andrea Murari (Entropy, 2021)

A systemic approach to classification for knowledge discovery with applications to the identification of boundary equations in complex systems. - Andrea Murari; Michela Gelfusa; Michele Lungaroni; Pasquale Gaudio; Emmanuele Peluso (Artif. Intell. Rev., 2022)

Complexity: Frontiers in Data-Driven Methods for Understanding, Prediction, and Control of Complex Systems 2022 on the Development of Information Theoretic Model Selection Criteria for the Analysis of Experimental Data. - Andrea Murari; Michele Lungaroni; Riccardo Rossi; Luca Spolladore; Michela Gelfusa (Complex., 2022)

Combining neural computation and genetic programming for observational causality detection and causal modelling. - Andrea Murari; Riccardo Rossi; Michela Gelfusa (Artif. Intell. Rev., 2023)

Upgrades of Genetic Programming for Data-Driven Modeling of Time Series. - Andrea Murari; Emmanuele Peluso; Luca Spolladore; Riccardo Rossi; Michela Gelfusa (Evol. Comput., 2023)

Information theoretic and neural computational tools for meta-analysis of cumulative databases in the age of Big Physics experiments. - Andrea Murari; Michele Lungaroni; Luca Spolladore; Emmanuele Peluso; Riccardo Rossi; Michela Gelfusa (Neural Comput. Appl., 2023)

Combining dimensional and statistical analysis for efficient data driven modelling of complex systems. - Andrea Murari; Luca Spolladore; Riccardo Rossi; Michela Gelfusa (Inf. Sci., 2023)

A practical utility-based but objective approach to model selection for regression in scientific applications. - Andrea Murari; Riccardo Rossi; Luca Spolladore; Michele Lungaroni; Pasquale Gaudio; Michela Gelfusa (Artif. Intell. Rev., 2023)

A deep learning framework for feature selection and dimensional analysis: Variational explainable neural networks. - Riccardo Rossi; Andrea Murari; Michela Gelfusa (Knowl. Based Syst., 2025)

Informed machine learning to reconcile interpretability with fidelity in scientific applications. - Andrea Murari; Riccardo Rossi; Luca Spolladore; Ivan Wyss; Michela Gelfusa (Artif. Intell. Rev., 2025)