97 citations · 170 across the 10 of their papers we have counts for
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cs.LG2021★ 1 cited
Deep Repulsive Prototypes for Adversarial Robustness
Alex Serban, Erik Poll, Joost Visser
While many defences against adversarial examples have been proposed, finding robust machine learning models is still an open problem. The most compelling defence to date is adversa…
cs.SE2021
Adapting Software Architectures to Machine Learning Challenges
Alex Serban, Joost Visser
Unique developmental and operational characteristics of ML components as well as their inherent uncertainty demand robust engineering principles are used to ensure their quality. W…
cs.SE2021
Practices for Engineering Trustworthy Machine Learning Applications
Alex Serban, Koen van der Blom, Holger Hoos +1
Following the recent surge in adoption of machine learning (ML), the negative impact that improper use of ML can have on users and society is now also widely recognised. To address…