activity
20132024
most citedLearning to detect RFI in radio astronomy without seeing it

29 citations · 81 across the 5 of their papers we have counts for

collaborators

6 papers

cs.AI2024★ 2 cited

Beyond the Veil of Similarity: Quantifying Semantic Continuity in Explainable AI

Qi Huang, Emanuele Mezzi, Osman Mutlu +5

We introduce a novel metric for measuring semantic continuity in Explainable AI methods and machine learning models. We posit that for models to be truly interpretable and trustwor…

astro-ph.IM2023★ 17 cited

The ROAD to discovery: machine learning-driven anomaly detection in radio astronomy spectrograms

Michael Mesarcik, Albert-Jan Boonstra, Marco Iacobelli +3

As radio telescopes increase in sensitivity and flexibility, so do their complexity and data-rates. For this reason automated system health management approaches are becoming incre…

astro-ph.IM2022★ 29 cited

Learning to detect RFI in radio astronomy without seeing it

Michael Mesarcik, Albert-Jan Boonstra, Elena Ranguelova +1

Radio Frequency Interference (RFI) corrupts astronomical measurements, thus affecting the performance of radio telescopes. To address this problem, supervised segmentation models h…

cs.LG2021★ 8 cited

Improving Novelty Detection using the Reconstructions of Nearest Neighbours

Michael Mesarcik, Elena Ranguelova, Albert-Jan Boonstra +1

We show that using nearest neighbours in the latent space of autoencoders (AE) significantly improves performance of semi-supervised novelty detection in both single and multi-clas…

astro-ph.IM2020★ 25 cited

Deep Learning Assisted Data Inspection for Radio Astronomy

Michael Mesarcik, Albert-Jan Boonstra, Christiaan Meijer +3

Modern radio telescopes combine thousands of receivers, long-distance networks, large-scale compute hardware, and intricate software. Due to this complexity, failures occur relativ…

q-fin.PM2013

Credit Portfolio Management in a Turning Rates Environment

Arthur M. Berd, Elena Ranguelova, Antonio Baldaque da Silva

We give a detailed account of correlations between credit sector/quality and treasury curve factors, using the robust framework of the Barclays POINT Global Risk Model. Consistent…