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  1. 1
    Building High-Throughput Neural Architecture Search Workflows via a Decoupled Fitness Prediction Engine

    Building High-Throughput Neural Architecture Search Workflows via a Decoupled Fitness Prediction Engine von Keller Rorabaugh, Ariel, Caino-Lores, Silvina, Johnston, Travis, Taufer, Michela


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  2. 2
    High frequency accuracy and loss data of random neural networks trained on image datasets

    High frequency accuracy and loss data of random neural networks trained on image datasets von Rorabaugh, Ariel Keller, Caíno-Lores, Silvina, Johnston, Travis, Taufer, Michela

    Veröffentlicht in Data in brief

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  3. 3
    Architecture Descriptions and High Frequency Accuracy and Loss Data of Random Neural Networks Trained on Image Datasets

    Architecture Descriptions and High Frequency Accuracy and Loss Data of Random Neural Networks Trained on Image Datasets von Keller Rorabaugh, Ariel, Caíno-Lores, Silvina, Wyatt II, Michael R., Johnston, Travis, Taufer, Michela

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  4. 4
    PEng4NN: An Accurate Performance Estimation Engine for Efficient Automated Neural Network Architecture Search

    PEng4NN: An Accurate Performance Estimation Engine for Efficient Automated Neural Network Architecture Search von Rorabaugh, Ariel Keller, Caíno-Lores, Silvina, WyattII, Michael R, Johnston, Travis, Taufer, Michela

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  5. 5
    PEng4NN: An Accurate Performance Estimation Engine for Efficient Automated Neural Network Architecture Search

    PEng4NN: An Accurate Performance Estimation Engine for Efficient Automated Neural Network Architecture Search von Ariel Keller Rorabaugh, Caíno-Lores, Silvina, Wyatt, Michael R, Johnston, Travis, Taufer, Michela

    Veröffentlicht in arXiv.org

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