Qiuyang Shen, Jiefu Chen, Xuqing Wu, Yueqin Huang, Zhu Han
Statistical Inversion of Electromagnetic Logging Data (eBook, PDF)
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Qiuyang Shen, Jiefu Chen, Xuqing Wu, Yueqin Huang, Zhu Han
Statistical Inversion of Electromagnetic Logging Data (eBook, PDF)
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Produktdetails
- Verlag: Springer Nature Switzerland
- Seitenzahl: 79
- Erscheinungstermin: 27. August 2020
- Englisch
- ISBN-13: 9783030570972
- Artikelnr.: 60067115
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
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Qiuyang Shen is a research scientist of Cyentech Consulting. He received his Bachelor's degree in telecommunication engineering from Huazhong University of Science and Technology, China, in 2015 and his Ph.D. degree in electrical engineering from University of Houston in 2019. His research interests include Bayesian inference, big data analysis, machine learning, and well logging. He has published over 10 technical journal and conference papers.
Jiefu Chen received his Ph.D. degree in electrical engineering from Duke University in 2010. He was a Staff Scientist with Advantage R&D Center, Weatherford International, from March 2011 to August 2015. Since then, he has been with University of Houston, where he is currently an Assistant Professor of Electrical and Computer Engineering. He has published more than 100 technical journal and conference papers on computational electromagnetics, subsurface wireless communication, and well logging.
Xuqing Wuis an Assistant Professor of Computer Information Systems in the College of Technology at the University of Houston. His research interests include machine learning, inverse problems, subsurface sensing, and computer vision. Prior to joining the University of Houston in 2015, he was a data scientist and modeling engineer at Schlumberger. He received his Ph.D. degree in Computer Science from the University of Houston.
Yueqin Huang received his Ph.D. degree in electrical engineering from Xiamen University, China, in 2011. She was an Assistant Professor with Xiamen University, Xiamen, China, from August 2011 to August 2012. Currently she is the Chief Scientist of Cyentech Consulting LLC, Cypress, TX. She has published more than 30 technical journal and conference papers on subsurface sensing and communication.
Zhu Han received his B.Sc in electronic engineering from Tsinghua University, in 1997, and his M.S. and Ph.D. degrees in electrical and computer engineering from the University of Maryland, College Park, in 1999 and 2003, respectively. From 2000 to 2008, he worked in industry and academic positions, including as an assistant professor at Boise State University, Idaho. Currently, he is a John and Rebecca Moores Professor in the Electrical and Computer Engineering Department as well as in the Computer Science Department at the University of Houston. His research interests include wireless resource allocation and management, wireless communications and networking, game theory, big data analysis, security, and smart grid. Dr Han has received several awards and best paper prizes including an NSF Career Award in 2010, the Fred W. Ellersick Prize of the IEEE Communication Society in 2011, and the IEEE Leonard G. Abraham Prize in the field of Communications Systems in 2016. Dr Han is IEEE fellow since 2014, AAAS fellow since 2019 and ACM distinguished member since 2019.
Jiefu Chen received his Ph.D. degree in electrical engineering from Duke University in 2010. He was a Staff Scientist with Advantage R&D Center, Weatherford International, from March 2011 to August 2015. Since then, he has been with University of Houston, where he is currently an Assistant Professor of Electrical and Computer Engineering. He has published more than 100 technical journal and conference papers on computational electromagnetics, subsurface wireless communication, and well logging.
Xuqing Wuis an Assistant Professor of Computer Information Systems in the College of Technology at the University of Houston. His research interests include machine learning, inverse problems, subsurface sensing, and computer vision. Prior to joining the University of Houston in 2015, he was a data scientist and modeling engineer at Schlumberger. He received his Ph.D. degree in Computer Science from the University of Houston.
Yueqin Huang received his Ph.D. degree in electrical engineering from Xiamen University, China, in 2011. She was an Assistant Professor with Xiamen University, Xiamen, China, from August 2011 to August 2012. Currently she is the Chief Scientist of Cyentech Consulting LLC, Cypress, TX. She has published more than 30 technical journal and conference papers on subsurface sensing and communication.
Zhu Han received his B.Sc in electronic engineering from Tsinghua University, in 1997, and his M.S. and Ph.D. degrees in electrical and computer engineering from the University of Maryland, College Park, in 1999 and 2003, respectively. From 2000 to 2008, he worked in industry and academic positions, including as an assistant professor at Boise State University, Idaho. Currently, he is a John and Rebecca Moores Professor in the Electrical and Computer Engineering Department as well as in the Computer Science Department at the University of Houston. His research interests include wireless resource allocation and management, wireless communications and networking, game theory, big data analysis, security, and smart grid. Dr Han has received several awards and best paper prizes including an NSF Career Award in 2010, the Fred W. Ellersick Prize of the IEEE Communication Society in 2011, and the IEEE Leonard G. Abraham Prize in the field of Communications Systems in 2016. Dr Han is IEEE fellow since 2014, AAAS fellow since 2019 and ACM distinguished member since 2019.
Introduction.- Foundation of Bayesian Inversion and Sampling Methods.- Beyond the Random Walk: a Hybrid Monte Carlo Sampling.- Interpret Model Complexity: Trans-Dimensional Markov Chain Monet Carlo Method.- Accelerated Bayesian Inversion Using Parallel Tempering
Introduction.- Foundation of Bayesian Inversion and Sampling Methods.- Beyond the Random Walk: a Hybrid Monte Carlo Sampling.- Interpret Model Complexity: Trans-Dimensional Markov Chain Monet Carlo Method.- Accelerated Bayesian Inversion Using Parallel Tempering