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Data Classification Using Carbon-Nanotubes and Evolutionary Algorithms.

, , , , , , and . PPSN, volume 9921 of Lecture Notes in Computer Science, page 644-654. Springer, (2016)

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Towards Intelligently Designed Evolvable Processors., , , , , , , , and . Evol. Comput., 30 (4): 479-501 (2022)Constructing Custom Thermodynamics Using Deep Learning., , , , , , , and . CoRR, (2023)Optimising Ferroelectric Thin Films with Evolutionary Computation., , and . GECCO Companion, page 783-786. ACM, (2023)Solving binary classification problems with carbon nanotube / liquid crystal composites and evolutionary algorithms., , , , , , and . CEC, page 1924-1931. IEEE, (2017)Computing Based on Material Training: Application to Binary Classification Problems., , , , , and . ICRC, page 1-8. IEEE, (2017)Training a Carbon-Nanotube/Liquid Crystal Data Classifier Using Evolutionary Algorithms., , , , , , and . UCNC, volume 9726 of Lecture Notes in Computer Science, page 130-141. Springer, (2016)Data Classification Using Carbon-Nanotubes and Evolutionary Algorithms., , , , , , and . PPSN, volume 9921 of Lecture Notes in Computer Science, page 644-654. Springer, (2016)Confidence Measures for Carbon-Nanotube / Liquid Crystals Classifiers., , , , , , and . CEC, page 1-8. IEEE, (2018)Constructing custom thermodynamics using deep learning., , , , , , , and . Nat. Comput. Sci., 4 (1): 66-85 (2024)