Bayesian history matching is a statistical method for calibrating complex computer models. The equations inside many scientific computer models contain parameters which have a true value, but that true value is often unknown; history matching is one technique for learning what these parameters could be. The name originates from the oil industry, where it refers to any technique for making sure oil reservoir models match up with historical oil production records. Since then, history matching has been widely used in many areas of science and engineering, including galaxy formation, disease modelling, climate science, and traffic simulation. The basis of history matching is to use observed data to rule-out any parameter settings which are ``implausible’’. Since computer models are often too slow to individually check every possible parameter setting, this is usually done with the help of an emulator. For a set of potential parameter settings , their implausibility can be calculated as: where is the expected output of the computer model for that parameter setting, and represents the uncertainties around the computer model output for that parameter setting. In other words, a parameter setting is scored based on how different the computer model output is to the real world observations, relative to how much uncertainty there is. For computer models that output only one value, an implausibility of 3 is considered a good threshold for rejecting parameter settings. For computer models which output more than one output, other thresholds can be used.A key component of history matching is the notion of iterative refocussing, where new computer model simulations can be chosen to better improve the emulator and the calibration, based on preliminary results. (Wikipedia).
History of computers - A Timeline
A timeline from the first computer, The Turing Machine, to the 1970's. Hope you guys enjoy,and make sure to subscribe and like! Adding subtitles for our video is welcomed! Your translation can help people around the world see our awesome videos! http://www.youtube.com/timedtext_cs_panel?c
From playlist Computers
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Viewers like you help make PBS (Thank you 😃) . Support your local PBS Member Station here: https://to.pbs.org/donateidea Are History & The Past Two Different Things? Tweet us! http://bit.ly/pbsideachanneltwitter Idea Channel Facebook! http://bit.ly/pbsideachannelfacebook Talk about this
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Look back at some of the photographs and photography installations that left their mark on history. Newsletter: https://www.history.com/newsletter Website - http://www.history.com /posts Facebook - https://www.facebook.com/History Twitter - https://twitter.com/history HISTORY Topical Vid
From playlist Examine the Past | History
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Applying History in Real Time: A Tale of Two Crises - Niall Ferguson
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Quantifying Uncertainty in Subsurface Systems
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From playlist Uncertainty Quantification
Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 12 - Fast Reinforcement Learning II
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai Professor Emma Brunskill, Stanford University http://onlinehub.stanford.edu/ Professor Emma Brunskill Assistant Professor, Computer Science Stanford AI for Hu
From playlist Stanford CS234: Reinforcement Learning | Winter 2019
Machine Learning @ Amazon by Rajeev Rastogi
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From playlist The Theoretical Basis of Machine Learning 2018 (ML)
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From playlist Machine Learning
War: Crash Course Statistics #42
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From playlist Statistical Rethinking Winter 2015
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From playlist Drawn History: Illustrations & Animations of Historical Events | History
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Introduction to New Testament (RLST 152) It is obvious that certain narratives in the New Testament contradict each other and cannot be woven into a historically coherent whole. How, then, do scholars construct who the "historical Jesus" was? There are several principles that historical
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