Tommaso Dorigo

According to our database, Tommaso Dorigo authored at least 8 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

TomOpt: differential optimisation for task- and constraint-aware design of particle detectors in the context of muon tomography.

Giles C. Strong, Maxime Lagrange, Aitor Orio, Anna Bordignon, Florian Bury, Tommaso Dorigo, Andrea Giammanco, Mariam Heikal, Jan Kieseler, Max Lamparth, Pablo Martínez Ruíz del Árbol, Federico Nardi, Pietro Vischia, Haitham Zaraket

Mach. Learn. Sci. Technol., 2024

Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference.

Luca Masserano, Alexander Shen, Michele Doro, Tommaso Dorigo, Rafael Izbicki, Ann B. Lee

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems.

Luca Masserano, Tommaso Dorigo, Rafael Izbicki, Mikael Kuusela, Ann B. Lee

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Simulation-Based Inference with WALDO: Perfectly Calibrated Confidence Regions Using Any Prediction or Posterior Estimation Algorithm.

Luca Masserano, Tommaso Dorigo, Rafael Izbicki, Mikael Kuusela, Ann B. Lee

CoRR, 2022

2021

The colours of the Higgs boson: a study in creativity and science motivation among high-school students in Italy.

Angelos N. Alexopoulos, Pier Stanislao Paolucci, Sofoklis A. Sotiriou, Franz Xaver Bogner, Tommaso Dorigo, Mariaelena Fedi, Dario Menasce, Michele Michelotto, Simone Paoletti, Francesca Scianitti

Smart Learn. Environ., 2021

Advanced Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider.

Anna Stakia, Tommaso Dorigo, Giovanni Banelli, Daniela Bortoletto, Alessandro Casa, Pablo de Castro, Christophe Delaere, Julien Donini, Livio Finos, Michele Gallinaro, Andrea Giammanco, Alexander Held, Fabricio Jiménez Morales, Grzegorz Kotkowski, Seng Pei Liew, Fabio Maltoni, Giovanna Menardi, Ioanna Papavergou, Alessia Saggio, Bruno Scarpa, Giles C. Strong, Cecilia Tosciri, João Varela, Pietro Vischia, Andreas Weiler

CoRR, 2021

2020

Dealing with Nuisance Parameters using Machine Learning in High Energy Physics: a Review.

Tommaso Dorigo, Pablo de Castro

CoRR, 2020

2019

INFERNO: Inference-Aware Neural Optimisation.

Pablo de Castro, Tommaso Dorigo

Comput. Phys. Commun., 2019