Launch week offerEnds in00h00m00s

annual Promonthly Pro

Roberta Siciliano

Docenti di ruolo di Ia fascia

Università degli Studi di Napoli Federico II

Italy

Research Interests

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Explore related searches

Professors in Italy Professors in Biostatistics Biostatistics professors in Italy

Articles (19)

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2022

Collaborators (8)

Pasquale Pagliano

Associate Professor

University of Salerno

ITALY

View details

Christian Riccio

Ricercatore Associato

Università degli Studi della Campania Luigi Vanvitelli

ITALY

View details

Gaetano Zazzaro

Centro Italiano Ricerche Aerospaziali

ITALY

View details

Francesco Galante

Adjunct professor for “Programming of Infrastructural Work-Zones”

University of Naples Federico II

ITALY

View details

Mark De Rooij

Professor

Leiden University

NETHERLANDS

View details

Maurizio Romano

Asssistant Professor

University of Cagliari

ITALY

View details

Andrea Saltelli

Academic Conselor

University of Bergen

NORWAY

View details

Antonio D'Ambrosio

Full Professor

University of Naples Federico II

ITALY

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Roberta Siciliano

Research Interests

Make your next move.

Explore related searches

Articles (19)

Synthetic Resampling Algorithm for Response Class Imbalance in Supervised Learning: Application to Road Accident Severity Prediction

A 3-level interpretable data-driven framework for operational analysis of industrial centrifugal pumps

Global Sensitivity Analysis for Robust XAI: Quantifying Clinical Risk and Prediction Instability in Dermoscopic Image Classification

Global sensitivity analysis in random forests: unveiling generative variable importance

Interpretable and robust tree-based methodology for imbalanced classification in driving safety assessment

Particle swarm optimization for preference rankings

Reduced rank regression for mixed predictor and response variables

Decoding Locomotor Intentions: Neural Networks and Probabilistic Machine Learning for Customizable Exoskeletons

Enhancing Statistical Inference in Mixed-Effect Three-Tree Model: A Data-Carving Estimation Strategy with an Application on Amyotrophic Lateral Sclerosis Data

Extending the Boosted-Oriented Probabilistic Clustering to the Unit Hypersphere: A Textual Data Perspective

From Prediction to Explanation: Interpreting Risk Factors in Health Survey Analytics

Predicting depression in Italy using random forest through the E2Tree methodology

Probabilistic Clustering for Hyperspherical Data: Extending the Boosted-Oriented Approach with a Textual Data Application

Portability rules detection by Epilepsy Tracking META-Set Analysis

Ideal Timing of Reimplantation in Patients with Periprosthetic Knee Infection Undergoing 2-Stage Exchange

Probabilistic Bayesian Neural Networks for olive phenology prediction in precision agriculture

The combined evaluation of fibrinogen and D-dimer levels are a helpful tool to exclude periprosthetic knee infection

Correction to: Boosted-oriented probabilistic smoothing-spline clustering of series (Statistical Methods & Applications, (2023), 32, 4, (1123-1140), 10.1007/s10260-022-00665-y)

Boosted-oriented probabilistic smoothing-spline clustering of series

Collaborators (8)

Pasquale Pagliano

Christian Riccio

Gaetano Zazzaro

Francesco Galante

Mark De Rooij

Maurizio Romano

Andrea Saltelli

Antonio D'Ambrosio

Make your next move.

Roberta Siciliano

Research Interests

Make your next move.

Explore related searches

Articles (19)

Synthetic Resampling Algorithm for Response Class Imbalance in Supervised Learning: Application to Road Accident Severity Prediction

A 3-level interpretable data-driven framework for operational analysis of industrial centrifugal pumps

Global Sensitivity Analysis for Robust XAI: Quantifying Clinical Risk and Prediction Instability in Dermoscopic Image Classification

Global sensitivity analysis in random forests: unveiling generative variable importance

Interpretable and robust tree-based methodology for imbalanced classification in driving safety assessment

Particle swarm optimization for preference rankings

Reduced rank regression for mixed predictor and response variables

Decoding Locomotor Intentions: Neural Networks and Probabilistic Machine Learning for Customizable Exoskeletons

Enhancing Statistical Inference in Mixed-Effect Three-Tree Model: A Data-Carving Estimation Strategy with an Application on Amyotrophic Lateral Sclerosis Data

Extending the Boosted-Oriented Probabilistic Clustering to the Unit Hypersphere: A Textual Data Perspective

From Prediction to Explanation: Interpreting Risk Factors in Health Survey Analytics

Predicting depression in Italy using random forest through the E2Tree methodology

Probabilistic Clustering for Hyperspherical Data: Extending the Boosted-Oriented Approach with a Textual Data Application

Portability rules detection by Epilepsy Tracking META-Set Analysis

Ideal Timing of Reimplantation in Patients with Periprosthetic Knee Infection Undergoing 2-Stage Exchange

Probabilistic Bayesian Neural Networks for olive phenology prediction in precision agriculture

The combined evaluation of fibrinogen and D-dimer levels are a helpful tool to exclude periprosthetic knee infection

Correction to: Boosted-oriented probabilistic smoothing-spline clustering of series (Statistical Methods &amp; Applications, (2023), 32, 4, (1123-1140), 10.1007/s10260-022-00665-y)

Boosted-oriented probabilistic smoothing-spline clustering of series

Collaborators (8)

Pasquale Pagliano

Christian Riccio

Gaetano Zazzaro

Francesco Galante

Mark De Rooij

Maurizio Romano

Andrea Saltelli

Antonio D'Ambrosio

Make your next move.

Correction to: Boosted-oriented probabilistic smoothing-spline clustering of series (Statistical Methods & Applications, (2023), 32, 4, (1123-1140), 10.1007/s10260-022-00665-y)