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Stanford Encyclopedia of Philosophy
Evolutionary psychology is one of many biologically informed approaches to the study of human behavior. Along with cognitive psychologists, evolutionary psychologists propose that much, if not all,Expand
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Continuous Time Bayesian Networks
TLDR
In this paper we present a language for finite state continuous time Bayesian networks (CTBNs), which describe structured stochastic processes that evolve over continuous time. Expand
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Learning Continuous Time Bayesian Networks
TLDR
Continuous time Bayesian networks describe structured stochastic processes with finitely many states that evolve over continuous time. Expand
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The Stanford Encyclopedia of Philosophy: A Developed Dynamic Reference Work
The present information explosion on the World Wide Web poses a problem for the general public and the members of an academic discipline alike, of how to find the most authoritative, comprehensive,Expand
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Expectation Maximization and Complex Duration Distributions for Continuous Time Bayesian Networks
TLDR
We present an algorithm, based on the Expectation Maximization (EM) algorithm (Dempster et al., 1977), for learning CTBN parameters from partially observable data. Expand
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Expectation Propagation for Continuous Time Bayesian Networks
TLDR
We describe an approximate inference algorithm for continuous time Bayesian networks that allows for general queries conditioned on evidence over continuous time intervals and at discrete time points. Expand
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Turing Machines
In 1 900 David Hilbert, the preeminent mathematician of his time, chal­ lenged the world of mathematics with a list of unsolved problems, pre­ sented in Paris before the International Congress of MExpand
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Reasoning at the Right Time Granularity
TLDR
We present a new expectation-propagation (EP) inference algorithm that utilizes a general cluster graph architecture where clusters contain distributions that can overlap in both space (set of variables) and time. Expand
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Continuous Time Bayesian Networks for Inferring Users’ Presence and Activities with Extensions for Modeling and Evaluation
TLDR
Continuous time Bayesian networks (CTBNs) describe structured stochastic processes with finitely many states that evolve over continuous time. Expand
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