5 citations · 9 across the 11 of their papers we have counts for
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cs.NE2024
AD-NEv++ : The multi-architecture neuroevolution-based multivariate anomaly detection framework
Marcin Pietroń, Dominik Żurek, Kamil Faber +1
Anomaly detection tools and methods enable key analytical capabilities in modern cyberphysical and sensor-based systems. Despite the fast-paced development in deep learning archite…
cs.NE2021★ 5 cited
Fast and scalable neuroevolution deep learning architecture search for multivariate anomaly detection
M. Pietroń, D. Żurek, K. Faber +1
Neuroevolution is one of the methodologies that can be used for learning optimal architecture during training. It uses evolutionary algorithms to generate the topology of artificia…