{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T18:44:06Z","timestamp":1761677046556,"version":"3.28.0"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"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":[[2021,12]]},"DOI":"10.1109\/icdm51629.2021.00081","type":"proceedings-article","created":{"date-parts":[[2022,1,24]],"date-time":"2022-01-24T21:04:04Z","timestamp":1643058244000},"page":"699-708","source":"Crossref","is-referenced-by-count":7,"title":["Global Convolutional Neural Processes"],"prefix":"10.1109","author":[{"given":"Xuesong","family":"Wang","sequence":"first","affiliation":[]},{"given":"Lina","family":"Yao","sequence":"additional","affiliation":[]},{"given":"Xianzhi","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Hye-Young","family":"Paik","sequence":"additional","affiliation":[]},{"given":"Sen","family":"Wang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"NIPS"},{"key":"ref11","first-page":"1704","article-title":"Conditional neural processes","author":"garnelo","year":"2018","journal-title":"International Conference on Machine Learning"},{"key":"ref12","article-title":"Deep convolutional networks as shallow gaussian processes","author":"garriga-alonso","year":"2018","journal-title":"International Conference on Learning Representations"},{"key":"ref13","first-page":"370","article-title":"Deep kernel learning","author":"wilson","year":"2016","journal-title":"Artificial Intelligence and Statistics"},{"journal-title":"Neural process family","year":"2020","author":"dubois","key":"ref14"},{"key":"ref15","first-page":"10 254","article-title":"Sequential neural processes","author":"singh","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.6056"},{"key":"ref17","article-title":"Time-series generative adversarial networks","author":"yoon","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref18","first-page":"9446","article-title":"Deep image prior","author":"ulyanov","year":"2018","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref19","first-page":"3012","article-title":"Image processing using multi-code gan prior","author":"gu","year":"2020","journal-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.chaos.2020.110121"},{"key":"ref3","article-title":"Residual attention u-net for automated multi-class segmentation of covid-19 chest ct images","author":"chen","year":"2020","journal-title":"arXiv preprint arXiv 2004 06774"},{"key":"ref6","article-title":"Neural processes","author":"garnelo","year":"2018","journal-title":"arXiv preprint arXiv 1807 01622"},{"key":"ref5","article-title":"When and how to lift the lockdown? global covid-19 scenario analysis and policy assessment using compartmental gaussian processes","volume":"33","author":"qian","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref8","article-title":"Meta-learning stationary stochastic process prediction with convolutional neural processes","volume":"33","author":"foong","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref7","article-title":"Attentive neural processes","author":"kim","year":"2018","journal-title":"International Conference on Learning Representations"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM50108.2020.00044"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM50108.2020.00057"},{"key":"ref9","article-title":"Convolutional conditional neural processes","author":"gordon","year":"2019","journal-title":"International Conference on Learning Representations"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00926"},{"journal-title":"Neural processes for sequential data","year":"2019","key":"ref22"},{"key":"ref21","article-title":"Task-agnostic online reinforcement learning with an infinite mixture of gaussian processes","volume":"33","author":"xu","year":"2020","journal-title":"Advances in neural information processing systems"}],"event":{"name":"2021 IEEE International Conference on Data Mining (ICDM)","start":{"date-parts":[[2021,12,7]]},"location":"Auckland, New Zealand","end":{"date-parts":[[2021,12,10]]}},"container-title":["2021 IEEE International Conference on Data Mining (ICDM)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9678506\/9678989\/09679110.pdf?arnumber=9679110","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T16:57:50Z","timestamp":1652201870000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9679110\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/icdm51629.2021.00081","relation":{},"subject":[],"published":{"date-parts":[[2021,12]]}}}