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This approach uses training data obtained through full\u2010wave EM simulations of a series of nanostructures to train geometric deep learning algorithms to assess the range of feasible responses as well as the feasibility of a desired response from a class of EM nanostructures. To facilitate the knowledge discovery, this approach combines the dimensionality reduction technique with convex\u2010hull and one\u2010class support\u2010vector\u2010machine (SVM) algorithms to find the range of the feasible responses in the latent response space of the EM nanostructure. More importantly, the one\u2010class SVM algorithm can be trained to provide the degree of feasibility of a response from a given nanostructure. This important information can be used to modify the initial structure to an alternative one that can enable an initially unfeasible response. To show the applicability of this approach, it is applied to two important classes of binary metasurfaces (MSs), formed by an array of plasmonic nanostructures, and periodic MSs formed by an array of dielectric nanopillars. These theoretical and experimental results confirm the unique features of this approach for knowledge discovery in EM nanostructures.<\/jats:p><\/jats:sec>","DOI":"10.1002\/aisy.201900132","type":"journal-article","created":{"date-parts":[[2019,12,5]],"date-time":"2019-12-05T04:33:24Z","timestamp":1575520404000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":94,"title":["Knowledge Discovery in Nanophotonics Using Geometric Deep Learning"],"prefix":"10.1002","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2805-2198","authenticated-orcid":false,"given":"Yashar","family":"Kiarashinejad","sequence":"first","affiliation":[{"name":"Georgia Institute of Technology  778 Atlantic Drive NW Atlanta GA 30332 USA"}]},{"given":"Mohammadreza","family":"Zandehshahvar","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology  778 Atlantic Drive NW Atlanta GA 30332 USA"}]},{"given":"Sajjad","family":"Abdollahramezani","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology  778 Atlantic Drive NW Atlanta GA 30332 USA"}]},{"given":"Omid","family":"Hemmatyar","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology  778 Atlantic Drive NW Atlanta GA 30332 USA"}]},{"given":"Reza","family":"Pourabolghasem","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology  778 Atlantic Drive NW Atlanta GA 30332 USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2628-0584","authenticated-orcid":false,"given":"Ali","family":"Adibi","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology  778 Atlantic Drive NW Atlanta GA 30332 USA"}]}],"member":"311","published-online":{"date-parts":[[2019,12,19]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6633\/aa8732"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1515\/nanoph-2017-0129"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/adom.201801709"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1364\/OPTICA.4.000139"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/nnano.2015.304"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1021\/acsphotonics.5b00660"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1364\/AOP.11.000518"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1364\/OL.41.003451"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1038\/nphoton.2017.93"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms15391"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1364\/OL.42.001197"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.aar2114"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.107.045901"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1002\/lpor.201400157"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMAG.2003.816248"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1021\/nn4057148"},{"key":"e_1_2_10_18_1","volume-title":"CLEO: QELS_Fundamental Science, FF1F\u20137","author":"Mansouree M.","year":"2018"},{"key":"e_1_2_10_19_1","doi-asserted-by":"crossref","unstructured":"M.Mansouree A.Arbabi International Applied Computational Electromagnetics Society Symposium (ACES) IEEE Miami FL2019 pp.1\u20132.","DOI":"10.23919\/ACES49320.2020.9196200"},{"key":"e_1_2_10_20_1","unstructured":"J.Jiang J. 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