The Case for Continuous Time

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Microsoft Research
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344,000
Published on ● Video Link: https://www.youtube.com/watch?v=Gj9NlYwTNIo


Duration: 1:14:21
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Time is a continuous quantity. This talk begins with theoretical and experimental problems that arise when time is treated as a discrete quantity in stochastic systems. I will then discuss continuous time Bayesian networks (CTBNs), a variable-based representation of continuous-time Markov processes. I will cover their representation and semantics and a bit about inference and learning in the models. Finally, I will present my group's recent work in employing CTBNs on real-world applications.



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