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representations in the form of ontologies, knowledge graphs, and neuro-symbolic learning, offering sound grounding also for Large Language Model (LLM) outcomes to drive knowledge-infused AI. The incorporation
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in HCAI in HumAIne is based on knowledge representations in the form of ontologies, knowledge graphs, and neuro-symbolic learning, offering sound grounding also for Large Language Model (LLM) outcomes
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affiliated knowledge institutes. Key areas of interest include Bayesian machine learning, probabilistic graphical models (factor graphs) and probabilistic programming. Where to apply Website https
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