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NeSySCALE: Scalable and Trustworthy Neuro-Symbolic AI through ε-Guaranteed Approximate Inference

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NeSySCALE: Scalable and Trustworthy Neuro-Symbolic AI through ε-Guaranteed Approximate Inference Deep learning has achieved remarkable success in tasks such as language generation, image classification, and speech recognition. However, these models remain largely opaque “black boxes,” making it difficult to understand or explain their predictions. This lack of interpretability limits their use in high-risk, regulated domains like healthcare or autonomous systems, where transparency and accountability are essential. The field of neuro-symbolic AI addresses this limitation by combining deep learning’s pattern recognition capabilities with the structured reasoning of symbolic AI. Neural probabilistic programming (NPP) is one such approach, integrating neural networks with probabilistic logic programs to produce models that are both powerful and interpretable. For example, in hospital risk monitoring of sepsis, NPP systems can transform raw medical data into probabilistic observations a

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award

status

SIGNED

region

EU

value

216240

unit

EUR