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Rik Adriaensen

@rik-a3.bsky.social
79 followers 110 following 5 posts
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Rik Adriaensen @rik-a3.bsky.social · 22/01/2026
Joint work with @lucasvanpraet.bsky.social, @jessabekker.bsky.social, @robinmanhaeve.bsky.social, Pieter Delobelle, and Maaten Buyl. Find the preprint at: arxiv.org/abs/2511.09768
arxiv.org
ProbLog4Fairness: A Neurosymbolic Approach to Modeling and Mitigating Bias
Operationalizing definitions of fairness is difficult in practice, as multiple definitions can be incompatible while each being arguably desirable. Instead, it may be easier to directly describe algor...
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Rik Adriaensen @rik-a3.bsky.social · 22/01/2026
💡 ProbLog4Fairness bridges this gap. It shows how to declaratively specify causes of bias using probabilistic logic in a principled, flexible, and interpretable way. Neurosymbolic extensions allow integrating these assumptions in the training of a classifier, to learn fair models from biased data!
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Rik Adriaensen @rik-a3.bsky.social · 22/01/2026
🔍 How to integrate fairness assumptions into ML models?
 In algorithmic fairness, many definitions of fairness exist, but they often contradict. Rather than choosing one definition, causal models reason about why bias arises in data. However, practitioners struggle to operationalize these models.
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Rik Adriaensen @rik-a3.bsky.social · 22/01/2026
📌 Tomorrow we present a poster on ProbLog4Fairness: A Neurosymbolic Approach to Modeling and Mitigating Bias at #AAAI (Machine Learning 2, poster 1233, 12pm - 2 pm).
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Rik Adriaensen @rik-a3.bsky.social · 22/01/2026
🔍 How to integrate fairness assumptions into ML models?
 In algorithmic fairness, many definitions of fairness exist, but they often contradict. Rather than choosing one definition, causal models reason about why bias arises in data. However, practitioners struggle to operationalize these models.
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