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most citedPhysics-Informed Real NVP for Satellite Power System Fault Detection

7 citations · 7 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.LG2025

Learning Robust Satellite Attitude Dynamics with Physics-Informed Normalising Flow

Carlo Cena, Mauro Martini, Marcello Chiaberge

Attitude control is a fundamental aspect of spacecraft operations. Model Predictive Control (MPC) has emerged as a powerful strategy for these tasks, relying on accurate models of…

cs.LG2025

Fault injection analysis of Real NVP normalising flow model for satellite anomaly detection

Gabriele Greco, Carlo Cena, Umberto Albertin +2

Satellites are used for a multitude of applications, including communications, Earth observation, and space science. Neural networks and deep learning-based approaches now represen…

cs.LG2024

Unsupervised Novelty Detection Methods Benchmarking with Wavelet Decomposition

Ariel Priarone, Umberto Albertin, Carlo Cena +2

Novelty detection is a critical task in various engineering fields. Numerous approaches to novelty detection rely on supervised or semi-supervised learning, which requires labelled…

cs.LG2024

A Self-Supervised Task for Fault Detection in Satellite Multivariate Time Series

Carlo Cena, Silvia Bucci, Alessandro Balossino +1

In the space sector, due to environmental conditions and restricted accessibility, robust fault detection methods are imperative for ensuring mission success and safeguarding valua…

cs.LG2024★ 7 cited

Physics-Informed Real NVP for Satellite Power System Fault Detection

Carlo Cena, Umberto Albertin, Mauro Martini +2

The unique challenges posed by the space environment, characterized by extreme conditions and limited accessibility, raise the need for robust and reliable techniques to identify a…