Symbolic regression
Showing all 9 results
-
Combining dimensional and statistical analysis for efficient data driven modelling of complex systems
Murari A.; Spolladore L.; Rossi R.; Gelfusa M. -
Upgrades of Genetic Programming for Data Driven Modelling of Time Series
Murari A.; Peluso E.; Spolladore L.; Rossi R.; Gelfusa M. -
Combining neural computation and genetic programming for observational causality detection and causal modelling
Murari A.; Rossi R.; Gelfusa M. -
Considerations on Stellarator’s Optimization from the Perspective of the Energy Confinement Time Scaling Laws
Murari A.; Peluso E.; Spolladore L.; Vega J.; Gelfusa M. -
Frontiers in data analysis methods: from causality detection to data driven experimental design
Murari, A.; Peluso, E.; Craciunescu, T.; Dormido-Canto, S.; Lungaroni, M.; Rossi, R.; Spolladore, L.; Vega, J.; Gelfusa, M. -
A systemic approach to classification for knowledge discovery with applications to the identification of boundary equations in complex systems
Murari A; Gelfusa M.; Lungaroni M.; Gauio P.; Peluso E. -
Scaling laws of the energy confinement time in stellarators without renormalization factors
Murari A.; Peluso E.; Vega J.; Garcia-Regana J.M.; Velasco J.L.; Fuchert G.; Gelfusa M. -
Investigating the Physics of Tokamak Global Stability with Interpretable Machine Learning Tools
Murari Andrea; Peluso Emmanuele; Lungaroni Michele; Rossi Riccardo; Gelfusa Michela; JET Contributors -
A New Approach to the Planning of New Experiments based on Learning in Non-Stationary Conditions
Murari A.; Lungaroni M.; Peluso E.; Gelfusa M.; Craciunescu T.; JET Contributors