Interpretable machine learning models: a physics-based view

22 Mar 2020Ion MateiJohan de KleerChristoforos SomarakisRahul RaiJohn S. Baras

To understand changes in physical systems and facilitate decisions, explaining how model predictions are made is crucial. We use model-based interpretability, where models of physical systems are constructed by composing basic constructs that explain locally how energy is exchanged and transformed... (read more)

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