{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T14:53:41Z","timestamp":1783436021215,"version":"3.54.6"},"reference-count":29,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,2,1]]},"DOI":"10.23919\/date51398.2021.9474253","type":"proceedings-article","created":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T00:30:23Z","timestamp":1628641823000},"page":"1372-1377","source":"Crossref","is-referenced-by-count":36,"title":["Parasitic-Aware Analog Circuit Sizing with Graph Neural Networks and Bayesian Optimization"],"prefix":"10.23919","author":[{"given":"Mingjie","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Walker J.","family":"Turner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"George F.","family":"Kokai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brucek","family":"Khailany","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David Z.","family":"Pan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haoxing","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAD45719.2019.8942062"},{"key":"ref11","article-title":"AutoCkt: Deep reinforcement learning of analog circuit designs","author":"settaluri","year":"2020","journal-title":"DATE"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAD.2013.6691100"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/DAC18072.2020.9218515"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/DAC18072.2020.9218495"},{"key":"ref15","first-page":"1","article-title":"A general approach for identifying hierarchical symmetry constraints for analog circuit layout","author":"kunal","year":"2020","journal-title":"ICCAD"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3394885.3431545"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3400302.3415624"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.23919\/DATE.2019.8714788"},{"key":"ref19","article-title":"Scalable bayesian optimization using deep neural networks","author":"snoek","year":"0","journal-title":"Machine Learning Research"},{"key":"ref28","article-title":"Deep graph library: A graph-centric, highly-performant package for graph neural networks","author":"wang","year":"2019","journal-title":"ArXiv Preprint"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TCSI.2017.2768826"},{"key":"ref27","author":"rapin","year":"2018","journal-title":"Nevergrad - A gradient-free optimization platform"},{"key":"ref3","article-title":"Fuzzy selection based differential evolution algorithm for analog cell sizing capturing imprecise human intentions","author":"liu","year":"2009","journal-title":"IEEE Congress on Evolutionary Computation"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/DAC18072.2020.9218757"},{"key":"ref29","article-title":"Scikit-learn: Machine learning in Python","author":"pedregosa","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"ref5","first-page":"1","article-title":"Closing the design loop: Bayesian optimization assisted hierarchical analog layout synthesis","author":"liu","year":"2020","journal-title":"DAC"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2011.2158732"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/DATE.2004.1268911"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/43.905671"},{"key":"ref9","article-title":"Layout-aware sizing of analog ics using floorplan routing estimates for parasitic extraction","author":"louren\u00e7o","year":"2015","journal-title":"DATE"},{"key":"ref1","author":"gielen","year":"1989","journal-title":"ESSCIRC"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1002\/asi.20591"},{"key":"ref22","article-title":"Dropout: A simple way to prevent neural networks from overfitting","author":"srivastava","year":"2014","journal-title":"Journal of Machine Learning Research"},{"key":"ref21","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref24","article-title":"Sequential model-based optimization for general algorithm configuration","author":"hutter","year":"0","journal-title":"International Conference on Learning and Intelligent Optimization"},{"key":"ref23","article-title":"Dropout as a bayesian approximation: Representing model uncertainty in deep learning","author":"gal","year":"0","journal-title":"Machine Learning Research"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICNN.1995.488968"},{"key":"ref25","article-title":"Understanding dropout","author":"baldi","year":"2013","journal-title":"Advances in neural information processing systems"}],"event":{"name":"2021 Design, Automation & Test in Europe Conference & Exhibition (DATE)","location":"Grenoble, France","start":{"date-parts":[[2021,2,1]]},"end":{"date-parts":[[2021,2,5]]}},"container-title":["2021 Design, Automation & Test in Europe Conference & Exhibition (DATE)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9473901\/9473226\/09474253.pdf?arnumber=9474253","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,28]],"date-time":"2022-01-28T21:15:15Z","timestamp":1643404515000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9474253\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2,1]]},"references-count":29,"URL":"https:\/\/doi.org\/10.23919\/date51398.2021.9474253","relation":{},"subject":[],"published":{"date-parts":[[2021,2,1]]}}}