Tree Neural Networks in HOL4

机译：HOL4中的树神经网络

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We present an implementation of tree neural networks within the proof assistant HOL4. Their architecture makes them naturally suited for approximating functions whose domain is a set of formulas. We measure the performance of our implementation and compare it with other machine learning predictors on the tasks of evaluating arithmetical expressions and estimating the truth of propositional formulas.

机译：我们在证明助手HOL4中提出了树形神经网络的实现。它们的体系结构使它们自然地适合于近似其域为一组公式的函数。我们评估实现的性能，并将其与其他机器学习预测器进行比较，以评估算术表达式和估计命题公式的真值。

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《International Conference on Intelligent Computer Mathematics》|2020年|278-283|共6页
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Thibault Gauthier;
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3. Tree-RNN: Tree structural recurrent neural network for network traffic classification [J] . Ren Xinming, Gu Huaxi, Wei Wenting Expert systems with applications . 2021,第Apra期

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4. Evolutionary design of neural network tree-integration of decision tree, neural network and GA [C] . Qiangfu Zhao Evolutionary Computation, 2001. Proceedings of the 2001 Congress on . 2001

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5. Converting a trained neural network to a decision tree DecText - decision tree extractor. [D] . Boz, Olcay. 2000

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Tree Neural Networks in HOL4

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