{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T15:24:26Z","timestamp":1780673066056,"version":"3.54.1"},"reference-count":62,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Multimedia"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/tmm.2021.3059169","type":"journal-article","created":{"date-parts":[[2021,2,17]],"date-time":"2021-02-17T01:17:27Z","timestamp":1613524647000},"page":"780-790","source":"Crossref","is-referenced-by-count":51,"title":["Dynamic Emotion Modeling With Learnable Graphs and Graph Inception Network"],"prefix":"10.1109","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8948-5216","authenticated-orcid":false,"given":"Amir","family":"Shirian","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2757-4923","authenticated-orcid":false,"given":"Subarna","family":"Tripathi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2167-4891","authenticated-orcid":false,"given":"Tanaya","family":"Guha","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2017.2713408"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2907271"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2020.3023632"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2018-1858"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3136755.3136763"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2018.06.003"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2928998"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2808760"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8683133"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2019.8756551"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11018-5_24"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-04167-0\\_33"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12328"},{"key":"ref14","first-page":"1263","article-title":"Neural message passing for quantum chemistry","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Gilmer","year":"2017"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.18178\/wcse.2019.06.016"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00121"},{"key":"ref17","first-page":"652","article-title":"PointNet: Deep learning on point sets for 3 d classification and segmentation","volume-title":"Proc. Conf. Comput. Vis. Pattern Recognit.","author":"Qi","year":"2017"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2016.2593800"},{"key":"ref19","first-page":"2014","article-title":"Learning convolutional neural networks for graphs","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Niepert","year":"2016"},{"key":"ref20","first-page":"1024","article-title":"Inductive representation learning on large graphs","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Hamilton","year":"2017"},{"key":"ref21","article-title":"Graph wavelet neural network","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Xu","year":"2019"},{"key":"ref22","article-title":"Spectral networks and locally connected networks on graphs","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Bruna","year":"2014"},{"key":"ref23","first-page":"3844","article-title":"Convolutional neural networks on graphs with fast localized spectral filtering","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Defferrard","year":"2016"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00583"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351049"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.01024"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00112"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00415"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2016.7477625"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/2993148.2997632"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.341"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.03.068"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/2647868.2654984"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2019-3252"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2017.7952552"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2018.8486564"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2017.8019296"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351039"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2019-2822"},{"key":"ref41","article-title":"Identifying emotions from walking using affective and deep features","author":"Randhavane","year":"2019"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i02.5490"},{"key":"ref43","article-title":"How powerful are graph neural networks","volume-title":"in Proc. Int. Conf. Learn. Representations","author":"Xu","year":"2019"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.4324\/9781410605337-29"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2008.927665"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICDEW.2006.145"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0196391"},{"key":"ref48","first-page":"4800","article-title":"Hierarchical graph representation learning with differentiable pooling","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ying","year":"2018"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2012.2189550"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2016.2588488"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/ACII.2019.8925444"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.167"},{"key":"ref53","first-page":"1021","volume-title":"Proc. Int. Conf. Comput. Vis.","author":"Bulat","year":"2017"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2005.06.042"},{"key":"ref55","article-title":"LSTM-based deep learning models for non-factoid answer selection","volume-title":"Proc. Int. Conf. Learn. Representations workshop","author":"Tan","year":"2016"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2016-692"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/s10579-008-9076-6"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2009-103"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/ACII.2009.5349350"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2018-1872"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0113647"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11782"}],"container-title":["IEEE Transactions on Multimedia"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6046\/9687854\/09354543.pdf?arnumber=9354543","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T22:53:30Z","timestamp":1704840810000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9354543\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":62,"URL":"https:\/\/doi.org\/10.1109\/tmm.2021.3059169","relation":{},"ISSN":["1520-9210","1941-0077"],"issn-type":[{"value":"1520-9210","type":"print"},{"value":"1941-0077","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}