1.0Microsoft Researchhttps://www.microsoft.com/en-us/researchEric Horvitzhttps://www.microsoft.com/en-us/research/people/horvitz/Uncertain Reasoning and Forecasting - Microsoft Researchrich600338<blockquote class="wp-embedded-content" data-secret="f3RwHsd4Gb"><a href="https://www.microsoft.com/en-us/research/publication/uncertain-reasoning-forecasting/">Uncertain Reasoning and Forecasting</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/publication/uncertain-reasoning-forecasting/embed/#?secret=f3RwHsd4Gb" width="600" height="338" title="“Uncertain Reasoning and Forecasting” — Microsoft Research" data-secret="f3RwHsd4Gb" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script type="text/javascript">
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We develop a probability forecasting methodology through a synthesis of Bayesian belief-network models and classical time-series analysis. By casting Bayesian time-series analyses as temporal belief-network problems, we introduce arbitrary dependency models that capture richer, and more realistic, models of dynamic dependencies. The richer models and associated computational methods allow us to move beyond rigid classical […]