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Deep learning inspired prognostics scheme for applications generating big data.

, , и . IJCNN, стр. 3296-3302. IEEE, (2017)

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Raghavan Vallur

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Hierarchical Mahalanobis Distance Clustering Based Technique for Prognostics in Applications Generating Big Data., и . SSCI, стр. 516-521. IEEE, (2015)Distributed Learning of Deep Sparse Neural Networks for High-dimensional Classification., , , и . IEEE BigData, стр. 1587-1592. IEEE, (2018)Direct Error Driven Learning for Classification in Applications Generating Big-Data., , и . Development and Analysis of Deep Learning Architectures, том 867 из Studies in Computational Intelligence, Springer, (2020)Forward Gradients for Data-Driven CFD Wall Modeling., , , и . CoRR, (2023)A Multi-step Nonlinear Dimension-reduction Approach with Applications to Bigdata., , и . INNS Conference on Big Data, том 144 из Procedia Computer Science, стр. 81-88. Elsevier, (2018)AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification., , , , , и . ICPR, стр. 1908-1914. IEEE, (2022)SF-SFD: Stochastic Optimization of Fourier Coefficients to Generate Space-Filling Designs., , и . WSC, стр. 3636-3646. IEEE, (2023)Direct Error Driven Learning for Deep Neural Networks with Applications to Bigdata., , и . INNS Conference on Big Data, том 144 из Procedia Computer Science, стр. 89-95. Elsevier, (2018)Deep learning inspired prognostics scheme for applications generating big data., , и . IJCNN, стр. 3296-3302. IEEE, (2017)A Multi-Step Nonlinear Dimension-Reduction Approach with Applications to Big Data., , и . IEEE Trans. Knowl. Data Eng., 31 (12): 2249-2261 (2019)