{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T07:38:28Z","timestamp":1763105908497,"version":"3.37.3"},"reference-count":68,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"7","license":[{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62132017"],"award-info":[{"award-number":["62132017"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["226-2022-00235"],"award-info":[{"award-number":["226-2022-00235"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Visual. Comput. Graphics"],"published-print":{"date-parts":[[2024,7]]},"DOI":"10.1109\/tvcg.2022.3230832","type":"journal-article","created":{"date-parts":[[2022,12,26]],"date-time":"2022-12-26T19:19:51Z","timestamp":1672082391000},"page":"3359-3373","source":"Crossref","is-referenced-by-count":3,"title":["Towards Efficient Visual Simplification of Computational Graphs in Deep Neural Networks"],"prefix":"10.1109","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9284-0477","authenticated-orcid":false,"given":"Rusheng","family":"Pan","sequence":"first","affiliation":[{"name":"Stake key Lab of CAD&#x0026;CG, Zhejiang University, Hangzhou, China"}]},{"given":"Zhiyong","family":"Wang","sequence":"additional","affiliation":[{"name":"Stake key Lab of CAD&#x0026;CG, Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0743-7558","authenticated-orcid":false,"given":"Yating","family":"Wei","sequence":"additional","affiliation":[{"name":"Stake key Lab of CAD&#x0026;CG, Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0450-1262","authenticated-orcid":false,"given":"Han","family":"Gao","sequence":"additional","affiliation":[{"name":"Distributed Data Lab, Huawei Technologies Co., Ltd., Shenzhen, China"}]},{"given":"Gongchang","family":"Ou","sequence":"additional","affiliation":[{"name":"Distributed Data Lab, Huawei Technologies Co., Ltd., Shenzhen, China"}]},{"given":"Caleb Chen","family":"Cao","sequence":"additional","affiliation":[{"name":"Distributed Data Lab, Huawei Technologies Co., Ltd., Shenzhen, China"}]},{"given":"Jingli","family":"Xu","sequence":"additional","affiliation":[{"name":"Stake key Lab of CAD&#x0026;CG, Zhejiang University, Hangzhou, China"}]},{"given":"Tong","family":"Xu","sequence":"additional","affiliation":[{"name":"Stake key Lab of CAD&#x0026;CG, Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8365-4741","authenticated-orcid":false,"given":"Wei","family":"Chen","sequence":"additional","affiliation":[{"name":"Stake key Lab of CAD&#x0026;CG, Zhejiang University, Hangzhou, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.04805"},{"year":"2020","key":"ref2","article-title":"The MindInsight repository on github"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3173574.3174237"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-27615-7_17"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220099"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/2678025.2701399"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2017.2744878"},{"year":"2016","key":"ref8","article-title":"The VisualDL repository on github"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2019.2934659"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2016.2598831"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/VAST.2017.8585721"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2017.2744158"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2018.2816223"},{"key":"ref14","first-page":"127","article-title":"Domain Model: Visualizing Concepts","author":"Larman","year":"2012","journal-title":"Applying UML and Patterns: An Introduction to Object Oriented Analysis and Design and Interative Development"},{"issue":"1","key":"ref15","first-page":"39","article-title":"Explainable Artificial Intelligence: Understanding, visualizing and interpreting deep learning models","volume":"1","author":"Samek","year":"2017","journal-title":"ITU J. ICT Discoveries"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2017.2744938"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2017.2744718"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2021.3057483"},{"article-title":"Keras","year":"2015","author":"Chollet","key":"ref19"},{"year":"2016","key":"ref20","article-title":"The draw-convnet repository on github"},{"year":"2018","key":"ref21","article-title":"The convnet-drawer repository on github"},{"key":"ref22","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Krizhevsky"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref26","first-page":"1","article-title":"Optimizing DNN computation with relaxed graph substitutions","volume-title":"Proc. Mach. Learn. Syst.","author":"Jia"},{"year":"2020","key":"ref27","article-title":"The MindSpore repository on github"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1609\/aimag.v40i2.2850"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.visinf.2017.01.006"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1111\/cgf.14034"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3359786"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s41095-020-0191-7"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2014.2346482"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2017.2744818"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2019.2934262"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2018.2865043"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2016.2598667"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2019.2952129"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/VISUAL.2005.1532820"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/s40687-022-00320-8"},{"year":"2017","key":"ref41","article-title":"The NETRON repository on github"},{"year":"2018","key":"ref42","article-title":"The HiddenLayer repository on github"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.1981.4308636"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.1986.6312901"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.7155\/jgaa.00122"},{"key":"ref46","first-page":"1","article-title":"Orthogonal grid drawing of clustered graphs","volume-title":"Proc. Graph Drawing","author":"Eades"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-62495-3_41"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/32.221135"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-58950-3_371"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-11805-0_14"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1145\/1456650.1456652"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1145\/230562.230577"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-8659.2011.01898.x"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/APVIS.2007.329288"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvlc.2005.10.003"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-44541-2_19"},{"issue":"1","key":"ref57","first-page":"1","article-title":"Exploring strategies for training deep neural networks","volume":"10","author":"Larochelle","year":"2009","journal-title":"J. Mach. Learn. Res."},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2008.34"},{"key":"ref59","first-page":"265","article-title":"TensorFlow: A system for large-scale machine learning","volume-title":"Proc. USENIX Conf. Operating Syst. Des. Implementation","author":"Abadi"},{"key":"ref60","first-page":"8026","article-title":"PyTorch: An imperative style, high-performance deep learning library","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Paszke"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2006.147"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2015.2467813"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1002\/spe.2179"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2011.185"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.l007\/978-3-319-46448-0_2"},{"key":"ref66","first-page":"1","article-title":"Very deep convolutional networks for large-scale image recognition","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Simonyan"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref68","first-page":"802","article-title":"Convolutional LSTM network: A machine learning approach for precipitation nowcasting","volume-title":"Proc. 28th Int. Conf. Neural Inf. Process. Syst.","author":"Shi"}],"container-title":["IEEE Transactions on Visualization and Computer Graphics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/2945\/10576039\/09999322.pdf?arnumber=9999322","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,29]],"date-time":"2024-06-29T05:34:08Z","timestamp":1719639248000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9999322\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7]]},"references-count":68,"journal-issue":{"issue":"7"},"URL":"https:\/\/doi.org\/10.1109\/tvcg.2022.3230832","relation":{},"ISSN":["1077-2626","1941-0506","2160-9306"],"issn-type":[{"type":"print","value":"1077-2626"},{"type":"electronic","value":"1941-0506"},{"type":"electronic","value":"2160-9306"}],"subject":[],"published":{"date-parts":[[2024,7]]}}}