{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T01:28:57Z","timestamp":1740101337610,"version":"3.37.3"},"reference-count":41,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,12,4]],"date-time":"2022-12-04T00:00:00Z","timestamp":1670112000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,12,4]],"date-time":"2022-12-04T00:00:00Z","timestamp":1670112000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100003141","name":"CONACYT","doi-asserted-by":"publisher","award":["CONACyT-A1-S-8216"],"award-info":[{"award-number":["CONACyT-A1-S-8216"]}],"id":[{"id":"10.13039\/501100003141","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008688","name":"CINVESTAV","doi-asserted-by":"publisher","award":["SEP-CINVESTAV-62,CNR-CINVESTAV"],"award-info":[{"award-number":["SEP-CINVESTAV-62,CNR-CINVESTAV"]}],"id":[{"id":"10.13039\/501100008688","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,12,4]]},"DOI":"10.1109\/ssci51031.2022.10022075","type":"proceedings-article","created":{"date-parts":[[2023,1,30]],"date-time":"2023-01-30T20:05:39Z","timestamp":1675109139000},"page":"442-447","source":"Crossref","is-referenced-by-count":1,"title":["Bayesian inference for neural network based high-precision modeling"],"prefix":"10.1109","author":[{"given":"Jorge","family":"Morales","sequence":"first","affiliation":[{"name":"CINVESTAV-IPN (National Polytechnic Institute),Departamento de Control Automático,Mexico City,Mexico"}]},{"given":"Wen","family":"Yu","sequence":"additional","affiliation":[{"name":"CINVESTAV-IPN,Departamento de Control Automático,Mexico City,Mexico"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/7503.003.0024"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1002\/9781118535561"},{"journal-title":"Mixture density networks","year":"1994","author":"Bishop","key":"ref3"},{"key":"ref4","article-title":"What is the state of neural network pruning?","author":"Davis","year":"2020","journal-title":"arXiv preprint"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/INDIN41052.2019.8972113"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CoDIT49905.2020.9263898"},{"volume-title":"Time series analysis: forecasting and control","year":"2015","author":"George EP","key":"ref7"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2015.24"},{"key":"ref9","volume-title":"Bayesian methods for nonlinear classification and regression","volume":"386","author":"Denison","year":"2002"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2016.2531674"},{"key":"ref11","article-title":"On fuzzy model identification and the gas furnace data","volume-title":"Proceedings of the IASTED International Conference Intelligent Systems and Control","author":"Wael","year":"2000"},{"key":"ref12","first-page":"25","article-title":"Training restricted Boltzmann machines: An introduction","volume":"1","author":"Asja","year":"2014","journal-title":"Pattern Recognition 47"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/0893-6080(94)00071-S"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2006.18.7.1527"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-92407-6"},{"key":"ref16","article-title":"Deep learning for sampling from arbitrary probability distributions","author":"Felix","year":"2018","journal-title":"arXiv preprint"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781139020411"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2005.12.126"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/17.8.754"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1093\/acprof:oso\/9780199216093.003.0002"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.2005.856649"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2014.01.008"},{"issue":"1998","key":"ref23","first-page":"2278","article-title":"Gradient-based learning applied to document recognition","volume-title":"Proceedings of the IEEE 86","volume":"11","author":"Yann"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/s11222-005-4786-8"},{"key":"ref25","volume-title":"Advanced Markov chain Monte Carlo methods: learning from past samples","volume":"714","author":"Faming","year":"2011"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2015.2499771"},{"issue":"2015","key":"ref27","first-page":"3195","article-title":"A variational Bayesian approach to robust identification of switched ARX models","volume":"12","author":"Yaojie","journal-title":"IEEE transactions on cybernetics 46"},{"article-title":"M\u00e9xico. Universidad Nacional Aut\u00f3noma de M\u00e9xico, I. d. G., Servicio Sismol\u00f3gico Nacional","volume-title":"Cat\u00e1logo de sismos. Retrieved from","year":"2020","key":"ref28"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1080\/01969722.2020.1814582"},{"issue":"2017","key":"ref30","first-page":"2948","article-title":"Data-driven finite-horizon approximate optimal control for discrete-time nonlinear systems using iterative HDP approach","volume":"10","author":"Chaoxu","journal-title":"IEEE transactions on cybernetics 48"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CIEL.2014.7015739"},{"key":"ref32","article-title":"Cascaded tanks benchmark combining soft and hard nonlinearities","volume-title":"Workshop on nonlinear system identi cation benchmarks","author":"Maarten","year":"2016"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.3969\/j.issn.1004-4132.2011.01.007"},{"key":"ref34","first-page":"51","article-title":"Bayesian probabilistic prediction of strong earthquakes in the main seismogenic zones of Greece","volume":"113","author":"Stavrakakis","year":"1987","journal-title":"Boll. Geofis. Teor. Applic"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1080\/08982110600653598"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.soildyn.2015.03.025"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-88518-4_88"},{"key":"ref38","article-title":"Neural Modeling With Guaranteed Input-Output Probability Distributions","author":"Wen","year":"2020","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics: Systems"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1177\/002029400303600703"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2011.2168538"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2006.10.030"}],"event":{"name":"2022 IEEE Symposium Series on Computational Intelligence (SSCI)","start":{"date-parts":[[2022,12,4]]},"location":"Singapore, Singapore","end":{"date-parts":[[2022,12,7]]}},"container-title":["2022 IEEE Symposium Series on Computational Intelligence (SSCI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10022049\/10022014\/10022075.pdf?arnumber=10022075","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T06:44:08Z","timestamp":1707806648000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10022075\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,4]]},"references-count":41,"URL":"https:\/\/doi.org\/10.1109\/ssci51031.2022.10022075","relation":{},"subject":[],"published":{"date-parts":[[2022,12,4]]}}}