{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T05:48:16Z","timestamp":1745300896715},"reference-count":13,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,12,17]],"date-time":"2022-12-17T00:00:00Z","timestamp":1671235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,12,17]],"date-time":"2022-12-17T00:00:00Z","timestamp":1671235200000},"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":[],"published-print":{"date-parts":[[2022,12,17]]},"DOI":"10.1109\/bigdata55660.2022.10020662","type":"proceedings-article","created":{"date-parts":[[2023,1,26]],"date-time":"2023-01-26T19:35:23Z","timestamp":1674761723000},"page":"4988-4992","source":"Crossref","is-referenced-by-count":1,"title":["BrainMixup: Data Augmentation for GNN-based Functional Brain Network Analysis"],"prefix":"10.1109","author":[{"given":"Alexis","family":"Li","sequence":"first","affiliation":[{"name":"Hamilton High School,Gilbert,United States of America"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Top applications of graph neural networks 2021","volume-title":"Criteo R&D Blog","author":"Ivanov","year":"2021"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17315"},{"article-title":"DropEdge: towards deep graph convolutional networks on node classification","year":"2020","author":"Rong","key":"ref3"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/access.2021.3111908"},{"article-title":"mixup: Beyond empirical risk minimization","year":"2018","author":"Zhang","key":"ref5"},{"article-title":"G-Mixup: Graph Data Augmentation for Graph Classification","year":"2022","author":"Han","key":"ref6"},{"key":"ref7","article-title":"nilearn.datasets.fetch_abide_pcp"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3326362"},{"author":"Chapelle","key":"ref9","article-title":"Vicinal Risk Minimization"},{"key":"ref10","article-title":"OpenNeuro"},{"article-title":"Masked label prediction: unified message passing model for semi-supervised slassification","author":"Shi","key":"ref11","doi-asserted-by":"crossref","DOI":"10.24963\/ijcai.2021\/214"},{"author":"Kipf","key":"ref12","article-title":"Semi-Supervised classification with graph convolutional networks"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i7.20767"}],"event":{"name":"2022 IEEE International Conference on Big Data (Big Data)","start":{"date-parts":[[2022,12,17]]},"location":"Osaka, Japan","end":{"date-parts":[[2022,12,20]]}},"container-title":["2022 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10020192\/10020156\/10020662.pdf?arnumber=10020662","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T08:00:49Z","timestamp":1707811249000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10020662\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,17]]},"references-count":13,"URL":"https:\/\/doi.org\/10.1109\/bigdata55660.2022.10020662","relation":{},"subject":[],"published":{"date-parts":[[2022,12,17]]}}}