Thomas Cecconello

According to our database, Thomas Cecconello authored at least 8 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

RADiff: Controllable Diffusion Models for Radio Astronomical Maps Generation.

Renato Sortino, Thomas Cecconello, Andrea DeMarco, Giuseppe Fiameni, Andrea Pilzer, Daniel Magro, Andrew M. Hopkins, Simone Riggi, Eva Sciacca, Adriano Ingallinera, Cristobal Bordiu, Filomena Bufano, Concetto Spampinato

IEEE Trans. Artif. Intell., December, 2024

Self-supervised learning for radio-astronomy source classification: a benchmark.

Thomas Cecconello, Simone Riggi, Ugo Becciani, Fabio Vitello, Andrew M. Hopkins, Giuseppe Vizzari, Concetto Spampinato, Simone Palazzo

CoRR, 2024

Classification of compact radio sources in the Galactic plane with supervised machine learning.

Simone Riggi, Grazia Umana, C. Trigilio, Cristobal Bordiu, Filomena Bufano, Adriano Ingallinera, F. Cavallaro, Yjan Gordon, Ray P. Norris, G. Gürkan, P. Leto, C. Buemi, S. Loru, Andrew M. Hopkins, Miroslav D. Filipovic, Thomas Cecconello

CoRR, 2024

2023

Astronomical source detection in radio continuum maps with deep neural networks.

Simone Riggi, Daniel Magro, Renato Sortino, Andrea DeMarco, Cristobal Bordiu, Thomas Cecconello, Andrew M. Hopkins, Joshua R. Marvil, Grazia Umana, Eva Sciacca, Fabio Vitello, Filomena Bufano, Adriano Ingallinera, Giuseppe Fiameni, Concetto Spampinato, Kristian Zarb Adami

Astron. Comput., January, 2023

Pedestrian Simulation with Reinforcement Learning: A Curriculum-Based Approach.

Giuseppe Vizzari, Thomas Cecconello

Future Internet, 2023

Curriculum-Based Reinforcement Learning for Pedestrian Simulation: Towards an Explainable Training Process?

Giuseppe Vizzari, Daniela Briola, Thomas Cecconello

Proceedings of the 24th Workshop "From Objects to Agents", 2023

2021

A Curriculum-Based Reinforcement Learning Approach to Pedestrian Simulation.

Thomas Albericci, Thomas Cecconello, Alberto Gibertini, Giuseppe Vizzari

Proceedings of the 22nd Workshop "From Objects to Agents", 2021

Unsupervised Data Pattern Discovery on the Cloud.

Thomas Cecconello, Lucas Puerari, Giuseppe Vizzari

Proceedings of the AIxIA 2021 Discussion Papers co-located with the the 20th International Conference of the Italian Association for Artificial Intelligence (AIxIA2021), 2021