{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T16:07:54Z","timestamp":1780589274766,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":68,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,4,25]],"date-time":"2022-04-25T00:00:00Z","timestamp":1650844800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2021ZD0112400"],"award-info":[{"award-number":["2021ZD0112400"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62102060"],"award-info":[{"award-number":["62102060"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,4,25]]},"DOI":"10.1145\/3487553.3524718","type":"proceedings-article","created":{"date-parts":[[2022,8,16]],"date-time":"2022-08-16T22:41:30Z","timestamp":1660689690000},"page":"1063-1072","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":25,"title":["Graph Augmentation Learning"],"prefix":"10.1145","author":[{"given":"Shuo","family":"Yu","sequence":"first","affiliation":[{"name":"School of Software, Dalian University of Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huafei","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Software, Dalian University of Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minh N.","family":"Dao","sequence":"additional","affiliation":[{"name":"School of Engineering, IT and Physical Sciences, Federation University Australia, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Xia","sequence":"additional","affiliation":[{"name":"School of Engineering, IT and Physical Sciences, Federation University Australia, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,8,16]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Proceedings of International Conference on Machine Learning, Vol.\u00a0139","author":"Cai Tianle","year":"2021","unstructured":"Tianle Cai , Shengjie Luo , Keyulu Xu , Di He , Tie-Yan Liu , and Liwei Wang . 2021 . GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training . In Proceedings of International Conference on Machine Learning, Vol.\u00a0139 . 1204\u20131215. Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, and Liwei Wang. 2021. GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training. In Proceedings of International Conference on Machine Learning, Vol.\u00a0139. 1204\u20131215."},{"key":"e_1_3_2_1_2_1","volume-title":"Fake Reviewer Group Detection in Online Review Systems. In International Conference on Data Mining Workshops. IEEE, 935\u2013942","author":"Cao Chen","year":"2021","unstructured":"Chen Cao , Shihao Li , Shuo Yu , and Zhikui Chen . 2021 . Fake Reviewer Group Detection in Online Review Systems. In International Conference on Data Mining Workshops. IEEE, 935\u2013942 . Chen Cao, Shihao Li, Shuo Yu, and Zhikui Chen. 2021. Fake Reviewer Group Detection in Online Review Systems. In International Conference on Data Mining Workshops. IEEE, 935\u2013942."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5747"},{"key":"e_1_3_2_1_4_1","volume-title":"Proceedings of International Conference on Machine Learning, Vol.\u00a0119","author":"Chen Ming","year":"2020","unstructured":"Ming Chen , Zhewei Wei , Zengfeng Huang , Bolin Ding , and Yaliang Li . 2020 . Simple and deep graph convolutional networks . In Proceedings of International Conference on Machine Learning, Vol.\u00a0119 . 1725\u20131735. Ming Chen, Zhewei Wei, Zengfeng Huang, Bolin Ding, and Yaliang Li. 2020. Simple and deep graph convolutional networks. In Proceedings of International Conference on Machine Learning, Vol.\u00a0119. 1725\u20131735."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3032189"},{"key":"e_1_3_2_1_6_1","volume-title":"Proceedings of Conference on Neural Information Processing Systems. 2224\u20132232","author":"Duvenaud David","year":"2015","unstructured":"David Duvenaud , Dougal Maclaurin , Jorge Aguilera-Iparraguirre , Rafael G\u00f3mez-Bombarelli , Timothy Hirzel , Al\u00e1n Aspuru-Guzik , and Ryan\u00a0 P. Adams . 2015 . Convolutional Networks on Graphs for Learning Molecular Fingerprints . In Proceedings of Conference on Neural Information Processing Systems. 2224\u20132232 . David Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre, Rafael G\u00f3mez-Bombarelli, Timothy Hirzel, Al\u00e1n Aspuru-Guzik, and Ryan\u00a0P. Adams. 2015. Convolutional Networks on Graphs for Learning Molecular Fingerprints. In Proceedings of Conference on Neural Information Processing Systems. 2224\u20132232."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2957786"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-acl.84"},{"key":"e_1_3_2_1_9_1","unstructured":"Zhan Gao Subhrajit Bhattacharya Leiming Zhang Rick\u00a0S. Blum Alejandro Ribeiro and Brian\u00a0M. Sadler. 2021. Training Robust Graph Neural Networks with Topology Adaptive Edge Dropping. CoRR abs\/2106.02892(2021).  Zhan Gao Subhrajit Bhattacharya Leiming Zhang Rick\u00a0S. Blum Alejandro Ribeiro and Brian\u00a0M. Sadler. 2021. Training Robust Graph Neural Networks with Topology Adaptive Edge Dropping. CoRR abs\/2106.02892(2021)."},{"key":"e_1_3_2_1_10_1","volume-title":"Proceedings of Conference on Neural Information Processing Systems. 1024\u20131034","author":"Hamilton L.","year":"2017","unstructured":"William\u00a0 L. Hamilton , Zhitao Ying , and Jure Leskovec . 2017 . Inductive Representation Learning on Large Graphs . In Proceedings of Conference on Neural Information Processing Systems. 1024\u20131034 . William\u00a0L. Hamilton, Zhitao Ying, and Jure Leskovec. 2017. Inductive Representation Learning on Large Graphs. In Proceedings of Conference on Neural Information Processing Systems. 1024\u20131034."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i03.5673"},{"key":"e_1_3_2_1_12_1","volume-title":"Proceedings of Conference on Neural Information Processing Systems.","author":"Hu Weihua","year":"2020","unstructured":"Weihua Hu , Matthias Fey , Marinka Zitnik , Yuxiao Dong , Hongyu Ren , Bowen Liu , Michele Catasta , and Jure Leskovec . 2020 . Open Graph Benchmark: Datasets for Machine Learning on Graphs . In Proceedings of Conference on Neural Information Processing Systems. Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, and Jure Leskovec. 2020. Open Graph Benchmark: Datasets for Machine Learning on Graphs. In Proceedings of Conference on Neural Information Processing Systems."},{"key":"e_1_3_2_1_13_1","volume-title":"Proceedings of International Conference on Learning Representations.","author":"Hu W","year":"2020","unstructured":"W Hu , B Liu , J Gomes , M Zitnik , P Liang , V Pande , and J Leskovec . 2020 . Strategies For Pre-training Graph Neural Networks . In Proceedings of International Conference on Learning Representations. W Hu, B Liu, J Gomes, M Zitnik, P Liang, V Pande, and J Leskovec. 2020. Strategies For Pre-training Graph Neural Networks. In Proceedings of International Conference on Learning Representations."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403237"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2018.8486369"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2015.2493549"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449914"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i9.16976"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403049"},{"key":"e_1_3_2_1_20_1","volume-title":"Proceedings of International Conference on Learning Representations.","author":"N.","unstructured":"Thomas\u00a0 N. Kipf and Max Welling. 2017. Semi-Supervised Classification with Graph Convolutional Networks . In Proceedings of International Conference on Learning Representations. Thomas\u00a0N. Kipf and Max Welling. 2017. Semi-Supervised Classification with Graph Convolutional Networks. In Proceedings of International Conference on Learning Representations."},{"key":"e_1_3_2_1_21_1","volume-title":"FLAG: Adversarial Data Augmentation for Graph Neural Networks. CoRR abs\/2010.09891(2020).","author":"Kong Kezhi","year":"2020","unstructured":"Kezhi Kong , Guohao Li , Mucong Ding , Zuxuan Wu , Chen Zhu , Bernard Ghanem , Gavin Taylor , and Tom Goldstein . 2020 . FLAG: Adversarial Data Augmentation for Graph Neural Networks. CoRR abs\/2010.09891(2020). Kezhi Kong, Guohao Li, Mucong Ding, Zuxuan Wu, Chen Zhu, Bernard Ghanem, Gavin Taylor, and Tom Goldstein. 2020. FLAG: Adversarial Data Augmentation for Graph Neural Networks. CoRR abs\/2010.09891(2020)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2019.01.029"},{"key":"e_1_3_2_1_23_1","first-page":"12","article-title":"A reduction of a graph to a canonical form and an algebra arising during this reduction","volume":"2","author":"Leman AA","year":"1968","unstructured":"AA Leman and Boris Weisfeiler . 1968 . A reduction of a graph to a canonical form and an algebra arising during this reduction . Nauchno-Technicheskaya Informatsiya 2 , 9 (1968), 12 \u2013 16 . AA Leman and Boris Weisfeiler. 1968. A reduction of a graph to a canonical form and an algebra arising during this reduction. Nauchno-Technicheskaya Informatsiya 2, 9 (1968), 12\u201316.","journal-title":"Nauchno-Technicheskaya Informatsiya"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11604"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401405"},{"key":"e_1_3_2_1_26_1","first-page":"1763","article-title":"Shifu2: A Network Representation Learning Based Model for Advisor-Advisee Relationship Mining","volume":"33","author":"Liu Jiaying","year":"2021","unstructured":"Jiaying Liu , Feng Xia , Lei Wang , Bo Xu , Xiangjie Kong , Hanghang Tong , and Irwin King . 2021 . Shifu2: A Network Representation Learning Based Model for Advisor-Advisee Relationship Mining . IEEE Transactions on Knowledge and Data Engineering 33 , 4(2021), 1763 \u2013 1777 . Jiaying Liu, Feng Xia, Lei Wang, Bo Xu, Xiangjie Kong, Hanghang Tong, and Irwin King. 2021. Shifu2: A Network Representation Learning Based Model for Advisor-Advisee Relationship Mining. IEEE Transactions on Knowledge and Data Engineering 33, 4(2021), 1763\u20131777.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403076"},{"key":"e_1_3_2_1_28_1","unstructured":"Xue Liu Dan Sun and Wei Wei. 2021. A Graph Data Augmentation Strategy with Entropy Preserving. CoRR abs\/2107.06048(2021).  Xue Liu Dan Sun and Wei Wei. 2021. A Graph Data Augmentation Strategy with Entropy Preserving. CoRR abs\/2107.06048(2021)."},{"key":"e_1_3_2_1_29_1","unstructured":"Yixin Liu Shirui Pan Ming Jin Chuan Zhou Feng Xia and Philip\u00a0S. Yu. 2021. Graph Self-Supervised Learning: A Survey. CoRR abs\/2103.00111(2021).  Yixin Liu Shirui Pan Ming Jin Chuan Zhou Feng Xia and Philip\u00a0S. Yu. 2021. Graph Self-Supervised Learning: A Survey. CoRR abs\/2103.00111(2021)."},{"key":"e_1_3_2_1_30_1","unstructured":"Weigang Lu Yibing Zhan Ziyu Guan Liu Liu Baosheng Yu Wei Zhao Yaming Yang and Dacheng Tao. 2021. SkipNode: On Alleviating Over-smoothing for Deep Graph Convolutional Networks. CoRR abs\/2112.11628(2021).  Weigang Lu Yibing Zhan Ziyu Guan Liu Liu Baosheng Yu Wei Zhao Yaming Yang and Dacheng Tao. 2021. SkipNode: On Alleviating Over-smoothing for Deep Graph Convolutional Networks. CoRR abs\/2112.11628(2021)."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16552"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441734"},{"key":"e_1_3_2_1_33_1","volume-title":"Proceedings of Conference on Neural Information Processing Systems, Vol.\u00a032","author":"Maron Haggai","year":"2019","unstructured":"Haggai Maron , Heli Ben-Hamu , Hadar Serviansky , and Yaron Lipman . 2019 . Provably Powerful Graph Networks . In Proceedings of Conference on Neural Information Processing Systems, Vol.\u00a032 . 2156\u20132167. Haggai Maron, Heli Ben-Hamu, Hadar Serviansky, and Yaron Lipman. 2019. Provably Powerful Graph Networks. In Proceedings of Conference on Neural Information Processing Systems, Vol.\u00a032. 2156\u20132167."},{"key":"e_1_3_2_1_34_1","volume-title":"Proceedings of Conference on Neural Information Processing Systems.","author":"Min Yimeng","year":"2020","unstructured":"Yimeng Min , Frederik Wenkel , and Guy Wolf . 2020 . Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks . In Proceedings of Conference on Neural Information Processing Systems. Yimeng Min, Frederik Wenkel, and Guy Wolf. 2020. Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks. In Proceedings of Conference on Neural Information Processing Systems."},{"key":"e_1_3_2_1_35_1","unstructured":"Christopher Morris Nils\u00a0M. Kriege Franka Bause Kristian Kersting Petra Mutzel and Marion Neumann. 2020. TUDataset: A collection of benchmark datasets for learning with graphs. CoRR abs\/2007.08663(2020).  Christopher Morris Nils\u00a0M. Kriege Franka Bause Kristian Kersting Petra Mutzel and Marion Neumann. 2020. TUDataset: A collection of benchmark datasets for learning with graphs. CoRR abs\/2007.08663(2020)."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014602"},{"key":"e_1_3_2_1_37_1","volume-title":"Proceedings of Conference on Neural Information Processing Systems.","author":"Papp P\u00e1l\u00a0Andr\u00e1s","year":"2021","unstructured":"P\u00e1l\u00a0Andr\u00e1s Papp , Karolis Martinkus , Lukas Faber , and Roger Wattenhofer . 2021 . DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks . In Proceedings of Conference on Neural Information Processing Systems. P\u00e1l\u00a0Andr\u00e1s Papp, Karolis Martinkus, Lukas Faber, and Roger Wattenhofer. 2021. DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks. In Proceedings of Conference on Neural Information Processing Systems."},{"key":"e_1_3_2_1_38_1","volume-title":"Proceedings of International Conference on Learning Representations.","author":"Rong Yu","year":"2020","unstructured":"Yu Rong , Wenbing Huang , Tingyang Xu , and Junzhou Huang . 2020 . DropEdge: Towards Deep Graph Convolutional Networks on Node Classification . In Proceedings of International Conference on Learning Representations. Yu Rong, Wenbing Huang, Tingyang Xu, and Junzhou Huang. 2020. DropEdge: Towards Deep Graph Convolutional Networks on Node Classification. In Proceedings of International Conference on Learning Representations."},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.5555\/2627435.2670313"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.6048"},{"key":"e_1_3_2_1_41_1","volume-title":"Proceedings of Conference on Neural Information Processing Systems.","author":"Suresh Susheel","year":"2021","unstructured":"Susheel Suresh , Pan Li , Cong Hao , and Jennifer Neville . 2021 . Adversarial Graph Augmentation to Improve Graph Contrastive Learning . In Proceedings of Conference on Neural Information Processing Systems. Susheel Suresh, Pan Li, Cong Hao, and Jennifer Neville. 2021. Adversarial Graph Augmentation to Improve Graph Contrastive Learning. In Proceedings of Conference on Neural Information Processing Systems."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2017.04.047"},{"key":"e_1_3_2_1_43_1","volume-title":"Proceedings of International Conference on Learning Representations.","author":"Velickovic Petar","year":"2018","unstructured":"Petar Velickovic , Guillem Cucurull , Arantxa Casanova , Adriana Romero , Pietro Li\u00f2 , and Yoshua Bengio . 2018 . Graph Attention Networks . In Proceedings of International Conference on Learning Representations. Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Li\u00f2, and Yoshua Bengio. 2018. Graph Attention Networks. In Proceedings of International Conference on Learning Representations."},{"key":"e_1_3_2_1_44_1","volume-title":"Proceedings of International Conference on Learning Representations.","author":"Velickovic Petar","year":"2019","unstructured":"Petar Velickovic , William Fedus , William\u00a0 L. Hamilton , Pietro Li\u00f2 , Yoshua Bengio , and R.\u00a0 Devon Hjelm . 2019 . Deep Graph Infomax . In Proceedings of International Conference on Learning Representations. Petar Velickovic, William Fedus, William\u00a0L. Hamilton, Pietro Li\u00f2, Yoshua Bengio, and R.\u00a0Devon Hjelm. 2019. Deep Graph Infomax. In Proceedings of International Conference on Learning Representations."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403177"},{"key":"e_1_3_2_1_46_1","unstructured":"Yiwei Wang Wei Wang Yuxuan Liang Yujun Cai and Bryan Hooi. 2020. GraphCrop: Subgraph Cropping for Graph Classification. CoRR abs\/2009.10564(2020).  Yiwei Wang Wei Wang Yuxuan Liang Yujun Cai and Bryan Hooi. 2020. GraphCrop: Subgraph Cropping for Graph Classification. CoRR abs\/2009.10564(2020)."},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403063"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/631"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAI.2021.3076021"},{"key":"e_1_3_2_1_50_1","unstructured":"Yaochen Xie Zhao Xu Zhengyang Wang and Shuiwang Ji. 2021. Self-Supervised Learning of Graph Neural Networks: A Unified Review. CoRR abs\/2102.10757(2021).  Yaochen Xie Zhao Xu Zhengyang Wang and Shuiwang Ji. 2021. Self-Supervised Learning of Graph Neural Networks: A Unified Review. CoRR abs\/2102.10757(2021)."},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/3383583.3398518"},{"key":"e_1_3_2_1_52_1","volume-title":"Proceedings of International Conference on Learning Representations.","author":"Xu Keyulu","year":"2018","unstructured":"Keyulu Xu , Weihua Hu , Jure Leskovec , and Stefanie Jegelka . 2018 . How Powerful are Graph Neural Networks? . In Proceedings of International Conference on Learning Representations. Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka. 2018. How Powerful are Graph Neural Networks?. In Proceedings of International Conference on Learning Representations."},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16588"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17283"},{"key":"e_1_3_2_1_55_1","volume-title":"Proceedings of International Conference on Machine Learning, Vol.\u00a0139","author":"You Yuning","year":"2021","unstructured":"Yuning You , Tianlong Chen , Yang Shen , and Zhangyang Wang . 2021 . Graph Contrastive Learning Automated . In Proceedings of International Conference on Machine Learning, Vol.\u00a0139 . 12121\u201312132. Yuning You, Tianlong Chen, Yang Shen, and Zhangyang Wang. 2021. Graph Contrastive Learning Automated. In Proceedings of International Conference on Machine Learning, Vol.\u00a0139. 12121\u201312132."},{"key":"e_1_3_2_1_56_1","volume-title":"Proceedings of Conference on Neural Information Processing Systems, Vol.\u00a033","author":"You Yuning","year":"2020","unstructured":"Yuning You , Tianlong Chen , Yongduo Sui , Ting Chen , Zhangyang Wang , and Yang Shen . 2020 . Graph contrastive learning with augmentations . In Proceedings of Conference on Neural Information Processing Systems, Vol.\u00a033 . 5812\u20135823. Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, and Yang Shen. 2020. Graph contrastive learning with augmentations. In Proceedings of Conference on Neural Information Processing Systems, Vol.\u00a033. 5812\u20135823."},{"key":"e_1_3_2_1_57_1","volume-title":"Proceedings of International Conference on Machine Learning, Vol.\u00a0119","author":"You Yuning","year":"2020","unstructured":"Yuning You , Tianlong Chen , Zhangyang Wang , and Yang Shen . 2020 . When Does Self-Supervision Help Graph Convolutional Networks? . In Proceedings of International Conference on Machine Learning, Vol.\u00a0119 . 10871\u201310880. Yuning You, Tianlong Chen, Zhangyang Wang, and Yang Shen. 2020. When Does Self-Supervision Help Graph Convolutional Networks?. In Proceedings of International Conference on Machine Learning, Vol.\u00a0119. 10871\u201310880."},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2021.3075955"},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3417446"},{"key":"e_1_3_2_1_60_1","unstructured":"Hanqing Zeng Muhan Zhang Yinglong Xia Ajitesh Srivastava Rajgopal Kannan Viktor\u00a0K. Prasanna Long Jin Andrey Malevich and Ren Chen. 2020. Deep Graph Neural Networks with Shallow Subgraph Samplers. CoRR abs\/2012.01380(2020).  Hanqing Zeng Muhan Zhang Yinglong Xia Ajitesh Srivastava Rajgopal Kannan Viktor\u00a0K. Prasanna Long Jin Andrey Malevich and Ren Chen. 2020. Deep Graph Neural Networks with Shallow Subgraph Samplers. CoRR abs\/2012.01380(2020)."},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17293"},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313527"},{"key":"e_1_3_2_1_63_1","volume-title":"Proceedings of Conference on Neural Information Processing Systems.","author":"Zhang Muhan","year":"2021","unstructured":"Muhan Zhang and Pan Li . 2021 . Nested Graph Neural Networks . In Proceedings of Conference on Neural Information Processing Systems. Muhan Zhang and Pan Li. 2021. Nested Graph Neural Networks. In Proceedings of Conference on Neural Information Processing Systems."},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17315"},{"key":"e_1_3_2_1_65_1","volume-title":"Proceedings of International Conference on Machine Learning, Vol.\u00a0119","author":"Zheng Cheng","year":"2020","unstructured":"Cheng Zheng , Bo Zong , Wei Cheng , Dongjin Song , Jingchao Ni , Wenchao Yu , Haifeng Chen , and Wei Wang . 2020 . Robust Graph Representation Learning via Neural Sparsification . In Proceedings of International Conference on Machine Learning, Vol.\u00a0119 . 11458\u201311468. Cheng Zheng, Bo Zong, Wei Cheng, Dongjin Song, Jingchao Ni, Wenchao Yu, Haifeng Chen, and Wei Wang. 2020. Robust Graph Representation Learning via Neural Sparsification. In Proceedings of International Conference on Machine Learning, Vol.\u00a0119. 11458\u201311468."},{"key":"e_1_3_2_1_66_1","unstructured":"Lecheng Zheng Dongqi Fu and Jingrui He. 2021. Tackling Oversmoothing of GNNs with Contrastive Learning. CoRR abs\/2110.13798(2021).  Lecheng Zheng Dongqi Fu and Jingrui He. 2021. Tackling Oversmoothing of GNNs with Contrastive Learning. CoRR abs\/2110.13798(2021)."},{"key":"e_1_3_2_1_67_1","volume-title":"Proceedings of Conference on Neural Information Processing Systems. 4917\u20134928","author":"Zhou Kaixiong","year":"2020","unstructured":"Kaixiong Zhou , Xiao Huang , Yuening Li , Daochen Zha , Rui Chen , and Xia Hu . 2020 . Towards Deeper Graph Neural Networks with Differentiable Group Normalization . In Proceedings of Conference on Neural Information Processing Systems. 4917\u20134928 . Kaixiong Zhou, Xiao Huang, Yuening Li, Daochen Zha, Rui Chen, and Xia Hu. 2020. Towards Deeper Graph Neural Networks with Differentiable Group Normalization. In Proceedings of Conference on Neural Information Processing Systems. 4917\u20134928."},{"key":"e_1_3_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449802"}],"event":{"name":"WWW '22: The ACM Web Conference 2022","location":"Virtual Event, Lyon France","acronym":"WWW '22","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Companion Proceedings of the Web Conference 2022"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3487553.3524718","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3487553.3524718","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:30:23Z","timestamp":1750188623000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3487553.3524718"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,25]]},"references-count":68,"alternative-id":["10.1145\/3487553.3524718","10.1145\/3487553"],"URL":"https:\/\/doi.org\/10.1145\/3487553.3524718","relation":{},"subject":[],"published":{"date-parts":[[2022,4,25]]},"assertion":[{"value":"2022-08-16","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}