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A multivariate regression approach for identification of SNPs importance in prostate cancer., , , , , и . J. Exp. Theor. Artif. Intell., 31 (6): 817-828 (2019)Missing Data Imputation for Continuous Variables Based on Multivariate Adaptive Regression Splines., , , , , , , , , и 3 other автор(ы). HAIS, том 12344 из Lecture Notes in Computer Science, стр. 73-85. Springer, (2020)Compensating atmospheric turbulence with CNNs for defocused pupil image wavefront sensors., , , , , , и . Log. J. IGPL, 29 (2): 180-192 (2021)Convolutional Neural Networks Approach for Solar Reconstruction in SCAO Configurations., , , , , и . Sensors, 19 (10): 2233 (2019)A Multiregressive Approach for SNPs Identification in Prostate Cancer., , , , , , , и . SOCO-CISIS-ICEUTE, том 649 из Advances in Intelligent Systems and Computing, стр. 400-409. Springer, (2017)Analysing the Performance of a Tomographic Reconstructor with Different Neural Networks Frameworks., , , , , и . ISDA, том 557 из Advances in Intelligent Systems and Computing, стр. 1051-1060. Springer, (2016)Early Fully-Convolutional Approach to Wavefront Imaging on Solar Adaptive Optics Simulations., , , , , , , , , и . HAIS, том 12344 из Lecture Notes in Computer Science, стр. 674-685. Springer, (2020)Using GPUs to Speed up a Tomographic Reconstructor Based on Machine Learning., , , , , и . SOCO-CISIS-ICEUTE, том 527 из Advances in Intelligent Systems and Computing, стр. 279-289. (2016)Improving Adaptive Optics Reconstructions with a Deep Learning Approach., , , , , , , и . HAIS, том 10870 из Lecture Notes in Computer Science, стр. 74-83. Springer, (2018)Compensating Atmospheric Turbulence with Convolutional Neural Networks for Defocused Pupil Image Wave-Front Sensors., , , , , , , и . HAIS, том 10870 из Lecture Notes in Computer Science, стр. 411-421. Springer, (2018)