{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:15:42Z","timestamp":1750220142172,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":13,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,8,14]],"date-time":"2022-08-14T00:00:00Z","timestamp":1660435200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,8,14]]},"DOI":"10.1145\/3534678.3542624","type":"proceedings-article","created":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T19:06:41Z","timestamp":1660331201000},"page":"4796-4797","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Frontiers of Graph Neural Networks with DIG"],"prefix":"10.1145","author":[{"given":"Shuiwang","family":"Ji","sequence":"first","affiliation":[{"name":"Texas A&M University, College Station, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meng","family":"Liu","sequence":"additional","affiliation":[{"name":"Texas A&M University, College Station, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Liu","sequence":"additional","affiliation":[{"name":"Texas A&M University, College Station, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Youzhi","family":"Luo","sequence":"additional","affiliation":[{"name":"Texas A&M University, College Station, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Limei","family":"Wang","sequence":"additional","affiliation":[{"name":"Texas A&M University, College Station, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaochen","family":"Xie","sequence":"additional","affiliation":[{"name":"Texas A&M University, College Station, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhao","family":"Xu","sequence":"additional","affiliation":[{"name":"Texas A&M University, College Station, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haiyang","family":"Yu","sequence":"additional","affiliation":[{"name":"Texas A&M University, College Station, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,8,14]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Peter W Battaglia Jessica B Hamrick Victor Bapst Alvaro Sanchez-Gonzalez Vinicius Zambaldi Mateusz Malinowski Andrea Tacchetti David Raposo Adam Santoro Ryan Faulkner et al. 2018. Relational inductive iases deep learning and graph networks. arXiv preprint arXiv:1806.01261 (2018)."},{"key":"e_1_3_2_1_2_1","volume-title":"International Conference on Learning Representations.","author":"Kipf Thomas N","year":"2017","unstructured":"Thomas N Kipf and Max Welling. 2017. Semi-supervised classification with graph convolutional networks. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_3_1","volume-title":"Proceedings of The 39th International Conference on Machine Learning.","author":"Liu Meng","year":"2022","unstructured":"Meng Liu, Youzhi Luo, Kanji Uchino, Koji Maruhashi, and Shuiwang Ji. 2022. Generating 3D molecules for target protein binding. In Proceedings of The 39th International Conference on Machine Learning."},{"key":"e_1_3_2_1_4_1","first-page":"1","article-title":"a. DIG: A Turnkey Library for Diving into Graph Deep Learning Research","volume":"22","author":"Liu Meng","year":"2021","unstructured":"Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Haiyang Yu, Zhao Xu, Jingtun Zhang, Yi Liu, Keqiang Yan, Haoran Liu, Cong Fu, Bora M Oztekin, Xuan Zhang, and Shuiwang Ji. 2021 a. DIG: A Turnkey Library for Diving into Graph Deep Learning Research. Journal of Machine Learning Research, Vol. 22, 240 (2021), 1--9. http:\/\/jmlr.org\/papers\/v22\/21-0343.html","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_5_1","volume-title":"GraphEBM: Molecular Graph Generation with Energy-Based Models. In Energy Based Models Workshop-ICLR","author":"Liu Meng","year":"2021","unstructured":"Meng Liu, Keqiang Yan, Bora Oztekin, and Shuiwang Ji. 2021 c. GraphEBM: Molecular Graph Generation with Energy-Based Models. In Energy Based Models Workshop-ICLR 2021."},{"key":"e_1_3_2_1_6_1","volume-title":"International Conference on Learning Representations.","author":"Liu Yi","year":"2021","unstructured":"Yi Liu, Limei Wang, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, and Shuiwang Ji. 2021 b. Spherical message passing for 3D molecular graphs. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_7_1","volume-title":"International Conference on Learning Representations.","author":"Luo Youzhi","year":"2021","unstructured":"Youzhi Luo and Shuiwang Ji. 2021. An autoregressive flow model for 3D molecular geometry generation from scratch. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_8_1","volume-title":"Proceedings of The 38th International Conference on Machine Learning. 7192--7203","author":"Luo Youzhi","year":"2021","unstructured":"Youzhi Luo, Keqiang Yan, and Shuiwang Ji. 2021. GraphDF: A Discrete Flow Model for Molecular Graph Generation. In Proceedings of The 38th International Conference on Machine Learning. 7192--7203."},{"key":"e_1_3_2_1_9_1","volume-title":"International Conference on Learning Representation.","author":"Petar Velivc","year":"2018","unstructured":"Petar Velivc kovi\u0107, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 2018. Graph attention networks. In International Conference on Learning Representation."},{"key":"e_1_3_2_1_10_1","volume-title":"Self-supervised learning of graph neural networks: A unified review","author":"Xie Yaochen","year":"2022","unstructured":"Yaochen Xie, Zhao Xu, Jingtun Zhang, Zhengyang Wang, and Shuiwang Ji. 2022. Self-supervised learning of graph neural networks: A unified review. IEEE Transactions on Pattern Analysis and Machine Intelligence (2022)."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403085"},{"key":"e_1_3_2_1_12_1","volume-title":"2020 b. Explainability in Graph Neural Networks: A Taxonomic Survey. arXiv preprint arXiv:2012.15445","author":"Yuan Hao","year":"2020","unstructured":"Hao Yuan, Haiyang Yu, Shurui Gui, and Shuiwang Ji. 2020 b. Explainability in Graph Neural Networks: A Taxonomic Survey. arXiv preprint arXiv:2012.15445 (2020)."},{"key":"e_1_3_2_1_13_1","volume-title":"Proceedings of The 38th International Conference on Machine Learning. 12241--12252","author":"Yuan Hao","year":"2021","unstructured":"Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, and Shuiwang Ji. 2021. On Explainability of Graph Neural Networks via Subgraph Explorations. In Proceedings of The 38th International Conference on Machine Learning. 12241--12252."}],"event":{"name":"KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"],"location":"Washington DC USA","acronym":"KDD '22"},"container-title":["Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3534678.3542624","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3534678.3542624","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:59:55Z","timestamp":1750186795000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3534678.3542624"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,14]]},"references-count":13,"alternative-id":["10.1145\/3534678.3542624","10.1145\/3534678"],"URL":"https:\/\/doi.org\/10.1145\/3534678.3542624","relation":{},"subject":[],"published":{"date-parts":[[2022,8,14]]},"assertion":[{"value":"2022-08-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}