{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T03:54:33Z","timestamp":1782964473154,"version":"3.54.5"},"reference-count":25,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100003130","name":"FWO, Belgium","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003130","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Smart Grid"],"published-print":{"date-parts":[[2023,9]]},"DOI":"10.1109\/tsg.2023.3243467","type":"journal-article","created":{"date-parts":[[2023,2,7]],"date-time":"2023-02-07T18:51:15Z","timestamp":1675795875000},"page":"4116-4124","source":"Crossref","is-referenced-by-count":13,"title":["Using Domain-Augmented Federated Learning to Model Thermostatically Controlled Loads"],"prefix":"10.1109","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7118-2927","authenticated-orcid":false,"given":"Attila","family":"Balint","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, KU Leuven, Leuven, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haroon","family":"Raja","sequence":"additional","affiliation":[{"name":"Electrical and Computer Engineering, Tufts University, Medford, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1025-0949","authenticated-orcid":false,"given":"Johan","family":"Driesen","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, KU Leuven, Leuven, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7765-8068","authenticated-orcid":false,"given":"Hussain","family":"Kazmi","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, KU Leuven, Leuven, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref13","author":"biewald","year":"2020","journal-title":"Experiment Tracking With Weights and Biases"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1561\/2200000083"},{"key":"ref15","article-title":"Flower: A friendly federated learning research framework","author":"beutel","year":"2020","journal-title":"arXiv 2007 14390"},{"key":"ref14","author":"abadi","year":"2015","journal-title":"TensorFlow Large-Scale Machine Learning on Heterogeneous Systems"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-01585-4"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/PowerTech46648.2021.9494834"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.enpol.2017.07.007"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2020.110120"},{"key":"ref17","article-title":"Time series data augmentation for deep learning: A survey","author":"wen","year":"2020","journal-title":"arXiv 2002 12478"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2019.01.140"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.3390\/sym10110648"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.enbuild.2019.02.016"},{"key":"ref24","author":"lundberg","year":"2023","journal-title":"A 'Unified Approach to Interpreting Model Predictions"},{"key":"ref23","first-page":"819","article-title":"Domain adaptation under target and conditional shift","author":"zhang","year":"2013","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00029"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-70604-3_2"},{"key":"ref22","author":"beutel","year":"2020","journal-title":"Flower A Friendly Federated Learning Research Framework[J]"},{"key":"ref21","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume":"54","author":"mcmahan","year":"2017","journal-title":"Proc 20th Int Conf Artif Intell Stat"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3328526.3329589"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/UPEC.2016.8113989"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s11750-022-00631-7"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2021.111290"},{"key":"ref3","author":"finck","year":"2018","journal-title":"Review of applied and tested control possibilities for energy flexibility in buildings"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2020.06.003"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.egyai.2021.100126"}],"container-title":["IEEE Transactions on Smart Grid"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5165411\/10226523\/10040618.pdf?arnumber=10040618","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,11]],"date-time":"2023-09-11T18:11:17Z","timestamp":1694455877000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10040618\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9]]},"references-count":25,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/tsg.2023.3243467","relation":{},"ISSN":["1949-3053","1949-3061"],"issn-type":[{"value":"1949-3053","type":"print"},{"value":"1949-3061","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9]]}}}