{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,12]],"date-time":"2025-01-12T05:09:20Z","timestamp":1736658560820,"version":"3.32.0"},"reference-count":26,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T00:00:00Z","timestamp":1733184000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T00:00:00Z","timestamp":1733184000000},"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","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,3]]},"DOI":"10.1109\/bibm62325.2024.10822221","type":"proceedings-article","created":{"date-parts":[[2025,1,10]],"date-time":"2025-01-10T20:12:45Z","timestamp":1736539965000},"page":"1552-1556","source":"Crossref","is-referenced-by-count":0,"title":["EMoNet: An environment causal learning for molecule OOD generalization"],"prefix":"10.1109","author":[{"given":"Limin","family":"Li","sequence":"first","affiliation":[{"name":"Univ. of Science & Technology of China,School of Software Engineering,Hefei,China"}]},{"given":"Kuo","family":"Yang","sequence":"additional","affiliation":[{"name":"Univ. of Science & Technology of China,School of Data Science,Hefei,China"}]},{"given":"Wenjie","family":"Du","sequence":"additional","affiliation":[{"name":"Univ. of Science & Technology of China,School of Software Engineering,Hefei,China"}]},{"given":"Zhongchao","family":"Yi","sequence":"additional","affiliation":[{"name":"Univ. of Science & Technology of China,School of Software Engineering,Hefei,China"}]},{"given":"Zhengyang","family":"Zhou","sequence":"additional","affiliation":[{"name":"Univ. of Science & Technology of China,School of Software Engineering,Hefei,China"}]},{"given":"Yang","family":"Wang","sequence":"additional","affiliation":[{"name":"Univ. of Science & Technology of China,School of Software Engineering,Hefei,China"}]}],"member":"263","reference":[{"year":"2016","author":"Alemi","journal-title":"Deep variational information bottleneck","key":"ref1"},{"doi-asserted-by":"publisher","key":"ref2","DOI":"10.1002\/wcms.1158"},{"year":"2024","author":"Cai","journal-title":"Latent graph diffusion: A unified framework for generation and prediction on graphs","key":"ref3"},{"key":"ref4","first-page":"36","article-title":"Does invariant graph learning via environment augmentation learn invariance?","author":"Chen","year":"2024","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref5","first-page":"22131","article-title":"Learning causally invariant representations for out-of-distribution generalization on graphs","volume":"35","author":"Chen","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1021\/jm00106a046"},{"key":"ref7","first-page":"31376","article-title":"Understanding and extending subgraph gnns by rethinking their symmetries","volume":"35","author":"Frasca","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref8","first-page":"30","article-title":"Inductive representation learning on large graphs","author":"Hamilton","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref9","first-page":"22118","article-title":"Open graph benchmark: Datasets for machine learning on graphs","volume":"33","author":"Hu","year":"2020","journal-title":"Advances in neural information processing systems"},{"year":"2016","author":"Jang","journal-title":"Categorical reparameterization with gumbel-softmax","key":"ref10"},{"doi-asserted-by":"publisher","key":"ref11","DOI":"10.1609\/aaai.v37i7.25970"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1609\/aaai.v38i8.28700"},{"year":"2016","author":"Kipf","journal-title":"Semi-supervised classification with graph convolutional networks","key":"ref13"},{"key":"ref14","first-page":"15524","article-title":"Interpretable and generalizable graph learning via stochastic attention mechanism","volume-title":"International Conference on Machine Learning","author":"Miao"},{"doi-asserted-by":"publisher","key":"ref15","DOI":"10.1109\/TPAMI.2023.3342184"},{"volume-title":"The Eleventh International Conference on Learning Representations","author":"Wang","article-title":"Searching lottery tickets in graph neural networks: A dual perspective","key":"ref16"},{"key":"ref17","first-page":"20437","article-title":"Graph information bottleneck","volume":"33","author":"Wu","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"volume-title":"International Conference on Learning Representations","author":"Wu","article-title":"Discovering invariant rationales for graph neural networks","key":"ref18"},{"year":"2018","author":"Xu","journal-title":"How powerful are graph neural networks?","key":"ref19"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.4155\/fmc-2018-0358"},{"doi-asserted-by":"publisher","key":"ref21","DOI":"10.1002\/wcms.1395"},{"doi-asserted-by":"publisher","key":"ref22","DOI":"10.1145\/3580305.3599339"},{"doi-asserted-by":"publisher","key":"ref23","DOI":"10.1109\/CVPR52688.2022.01879"},{"year":"2020","author":"Yu","journal-title":"Graph information bottleneck for subgraph recognition","key":"ref24"},{"key":"ref25","first-page":"26911","article-title":"Learning from counterfactual links for link prediction","volume-title":"International Conference on Machine Learning","author":"Zhao"},{"year":"2022","author":"Zheng","article-title":"Graph neural networks for graphs with heterophily: A survey","key":"ref26"}],"event":{"name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","start":{"date-parts":[[2024,12,3]]},"location":"Lisbon, Portugal","end":{"date-parts":[[2024,12,6]]}},"container-title":["2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10821710\/10821711\/10822221.pdf?arnumber=10822221","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,11]],"date-time":"2025-01-11T09:56:19Z","timestamp":1736589379000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10822221\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,3]]},"references-count":26,"URL":"https:\/\/doi.org\/10.1109\/bibm62325.2024.10822221","relation":{},"subject":[],"published":{"date-parts":[[2024,12,3]]}}}