A Machine Learning Method for Extracting Symbolic Knowledge from Recurrent Neural Networks von Vahed, A, Omlin, C. W

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Stable Encoding of Large Finite-State Automata in Recurrent Neural Networks with Sigmoid Discriminants von Omlin, Christian W., Giles, C. Lee

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Rule revision with recurrent neural networks von Omlin, C.W., Giles, C.L.

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Extraction of rules from discrete-time recurrent neural networks von Omlin, Christian W., Giles, C.Lee

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Constructing deterministic finite-state automata in recurrent neural networks von OMLIN, C. W, GILES, C. L

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Equivalence in knowledge representation: automata, recurrent neural networks, and dynamical fuzzy systems von Giles, C.L., Omlin, C.W., Thornber, K.K.

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Fuzzy finite-state automata can be deterministically encoded into recurrent neural networks von Omlin, C.W., Thornber, K.K., Giles, C.L.

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Inductive bias strength in knowledge-based neural networks: application to magnetic resonance spectroscopy of breast tissues von Omlin, Christian W., Snyders, Sean

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Equivalence in knowledge representation : Automata, recurrent neural networks, and dynamical fuzzy systems : Special issue on computational intelligence von GILES, C. L, OMLIN, C. W, THORNBER, K. K

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Pruning recurrent neural networks for improved generalization performance von Giles, C.L., Omlin, C.W.

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What inductive bias gives good neural network training performance? von Snyders, S., Omlin, C.W.

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Refining hidden Markov models with recurrent neural networks von Wessels, T., Omlin, C.W.

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Extraction, Insertion and Refinement of Symbolic Rules in Dynamically Driven Recurrent Neural Networks von GILES, C. LEE, OMLIN, CHRISTIAN W.

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Inductive bias in recurrent neural networks von SNYDERS, S, OMLIN, C. W

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Impacts and cost of faults on services in cellular networks von Kogeda, O.P., Agbinya, J.I., Omlin, C.W.

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Extraction, insertion and refinement of symbolic rules in dynamically driven recurrent neural networks: Architectures for integrating neural and symbolic process von LEE GILES, C, OMLIN, C. W

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Fuzzy Knowledge and Recurrent Neural Networks: A Dynamical Systems Perspective von Omlin, Christian W., Giles, Lee, Thornber, K. K.

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A hybrid system for signature verification von WESSELS, T, OMLIN, C. W

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What inductive bias gives good neural network training performance? von SNYDERS, S, OMLIN, C. W

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Refining hidden Markov models with recurrent neural networks von WESSELS, T, OMLIN, C. W

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