19 citations · 30 across the 5 of their papers we have counts for
3 papers · 1 filter
A Meta-Learning Algorithm for Interrogative Agendas
Erman Acar, Andrea De Domenico, Krishna Manoorkar +1
Explainability is a key challenge and a major research theme in AI research for developing intelligent systems that are capable of working with humans more effectively. An obvious…
Analyzing Differentiable Fuzzy Implications
Emile van Krieken, Erman Acar, Frank van Harmelen
Combining symbolic and neural approaches has gained considerable attention in the AI community, as it is often argued that the strengths and weaknesses of these approaches are comp…
Semi-Supervised Learning using Differentiable Reasoning
Emile van Krieken, Erman Acar, Frank van Harmelen
We introduce Differentiable Reasoning (DR), a novel semi-supervised learning technique which uses relational background knowledge to benefit from unlabeled data. We apply it to the…