End-to-end Differentiable Proving
نویسندگان
چکیده
● Architecture allows us to induce rules of predefined structure ● We can, for instance, incorporate the inductive bias of a transitivity relationship in the knowledge base θ1(X,Y) :θ2(X,Z), θ3(Z,Y). ● θi are vector representations for unknown predicates ● They can be learned like all other vector representations ● They can be decoded at test time by finding the closest known relation using the RBF kernel ● Rule confidence is minimum RBF similarity over all decodings ● Confidence is an upper bound on the proof success that can be achieved when applying the induced rule
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