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cs.LG2026
Traceable Spectral Inference via Influence Functions: Efficient Data Attribution and Error Proxies for the Ariel Mission
Nikki Grens, Luís F. Simões, Kai Hou Yip +1
Interpretability is critical for machine learning models deployed in scientific space missions such as ESA's Ariel, where ground truth is unavailable during operations and physical…
cs.LG2024
Operational range bounding of spectroscopy models with anomaly detection
Luís F. Simões, Pierluigi Casale, Marília Felismino +4
Safe operation of machine learning models requires architectures that explicitly delimit their operational ranges. We evaluate the ability of anomaly detection algorithms to provid…