95 citations · 697 across the 32 of their papers we have counts for
4 papers · 1 filter
Operational Range Bounding in Spectroscopy: A Safety Cage Framework for Machine Learning Models
Nikki Grens, Luís F. Simões, Kai Hou Yip +1
Ensuring the reliability of black-box machine learning models in safety-critical space missions remains a significant challenge, particularly when ground-truth is unavailable for v…
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…
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…
Conservative Policy Construction Using Variational Autoencoders for Logged Data with Missing Values
Mahed Abroshan, Kai Hou Yip, Cem Tekin +1
In high-stakes applications of data-driven decision making like healthcare, it is of paramount importance to learn a policy that maximizes the reward while avoiding potentially dan…