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The DeepLog Neurosymbolic Machine
Vincent Derkinderen, Robin Manhaeve, Rik Adriaensen +4
We contribute a theoretical and operational framework for neurosymbolic AI called DeepLog. DeepLog introduces building blocks and primitives for neurosymbolic AI that make abstract…
ProbLog4Fairness: A Neurosymbolic Approach to Modeling and Mitigating Bias
Rik Adriaensen, Lucas Van Praet, Jessa Bekker +3
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 dir…
DeepGraphLog for Layered Neurosymbolic AI
Adem Kikaj, Giuseppe Marra, Floris Geerts +2
Neurosymbolic AI (NeSy) aims to integrate the statistical strengths of neural networks with the interpretability and structure of symbolic reasoning. However, current NeSy framewor…
Declarative Design of Neural Predicates in Neuro-Symbolic Systems
Tilman Hinnerichs, Robin Manhaeve, Giuseppe Marra +1
Neuro-symbolic systems (NeSy), which claim to combine the best of both learning and reasoning capabilities of artificial intelligence, are missing a core property of reasoning syst…
ULLER: A Unified Language for Learning and Reasoning
Emile van Krieken, Samy Badreddine, Robin Manhaeve +1
The field of neuro-symbolic artificial intelligence (NeSy), which combines learning and reasoning, has recently experienced significant growth. There now are a wide variety of NeSy…
Semirings for Probabilistic and Neuro-Symbolic Logic Programming
Vincent Derkinderen, Robin Manhaeve, Pedro Zuidberg Dos Martires +1
The field of probabilistic logic programming (PLP) focuses on integrating probabilistic models into programming languages based on logic. Over the past 30 years, numerous languages…