{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T15:54:30Z","timestamp":1778082870787,"version":"3.51.4"},"reference-count":29,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,12,13]],"date-time":"2023-12-13T00:00:00Z","timestamp":1702425600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,12,13]],"date-time":"2023-12-13T00:00:00Z","timestamp":1702425600000},"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":[[2023,12,13]]},"DOI":"10.1109\/cdc49753.2023.10383587","type":"proceedings-article","created":{"date-parts":[[2024,1,19]],"date-time":"2024-01-19T18:38:36Z","timestamp":1705689516000},"page":"342-349","source":"Crossref","is-referenced-by-count":6,"title":["Uncertainty Quantification for Learning-based MPC using Weighted Conformal Prediction"],"prefix":"10.1109","author":[{"given":"Kong Yao","family":"Chee","sequence":"first","affiliation":[{"name":"University of Pennsylvania,Philadelphia,PA,USA,19104"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M. Ani","family":"Hsieh","sequence":"additional","affiliation":[{"name":"University of Pennsylvania,Philadelphia,PA,USA,19104"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"George J.","family":"Pappas","sequence":"additional","affiliation":[{"name":"University of Pennsylvania,Philadelphia,PA,USA,19104"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-control-090419-075625"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.23919\/ACC53348.2022.9867643"},{"issue":"3","key":"ref3","volume-title":"Gaussian processes for machine learning","volume":"2","author":"Williams","year":"2006"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2019.2926677"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3061307"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/37.466261"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989202"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.3390\/math9161912"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2019.119866"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3144787"},{"key":"ref11","first-page":"1125","article-title":"Learning-enhanced nonlin-ear model predictive control using knowledge-based neural ordinary differential equations and deep ensembles","volume-title":"Learning for Dynamics and Control Conference","author":"Chee","year":"2023"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.5555\/3045390.3045502"},{"key":"ref13","author":"Sun","year":"2019","journal-title":"Functional variational bayesian neural networks"},{"key":"ref14","article-title":"Simple and scalable predictive uncertainty estimation using deep ensembles","volume":"30","author":"Lakshminarayanan","year":"2017","journal-title":"Advances in neural Info. process. Syst."},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/b106715"},{"key":"ref16","first-page":"1660","article-title":"Adaptive conformal inference under distribution shift","volume":"34","author":"Gibbs","year":"2021","journal-title":"Advances in Neural Info. process. Syst."},{"key":"ref17","first-page":"11559","article-title":"Conformal prediction interval for dynamic time-series","volume-title":"Int. Conf. on Machine Learning","author":"Xu","year":"2021"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1214\/23-aos2276"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/lra.2023.3292071"},{"key":"ref20","first-page":"300","article-title":"Adaptive conformal prediction for motion planning among dynamic agents","volume-title":"Learning for Dynamics and Control Conference","author":"Dixit","year":"2023"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2003.823141"},{"key":"ref22","author":"Paszke","year":"2017","journal-title":"Automatic differen-tiation in pytorch"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.2307\/1913643"},{"key":"ref24","first-page":"345","article-title":"Induc-tive confidence machines for regression","volume-title":"Machine Learning: ECML 2002: 13th European Conference on Machine Learning Helsinki, Finland, August 19\u201323, 2002 Proceedings 13","author":"Papadopoulos","year":"2002"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ASSPCC.2000.882463"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.automatica.2014.10.128"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.1983.6313077"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s12532-018-0139-4"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-004-0559-y"}],"event":{"name":"2023 62nd IEEE Conference on Decision and Control (CDC)","location":"Singapore, Singapore","start":{"date-parts":[[2023,12,13]]},"end":{"date-parts":[[2023,12,15]]}},"container-title":["2023 62nd IEEE Conference on Decision and Control (CDC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10383192\/10383193\/10383587.pdf?arnumber=10383587","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,23]],"date-time":"2024-01-23T16:19:53Z","timestamp":1706026793000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10383587\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,13]]},"references-count":29,"URL":"https:\/\/doi.org\/10.1109\/cdc49753.2023.10383587","relation":{},"subject":[],"published":{"date-parts":[[2023,12,13]]}}}