A weighted sum over binary logic-rule activations lets Differentiable Logic Networks perform tabular regression with accuracy close to random forests at much lower inference cost.
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Learning Interpretable Differentiable Logic Networks for Tabular Regression
A weighted sum over binary logic-rule activations lets Differentiable Logic Networks perform tabular regression with accuracy close to random forests at much lower inference cost.