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for helping humans meet this challenge are causal Bayesian networks, which can accurately model complex probabilistic systems. However, because people are notoriously deficient in probabilistic reasoning
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The brain is a complex system and monitoring and imaging methods to observe critical neurophysiological variables underlying brain function are limited. This project works at the intersection
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The brain is a complex machine and brain function remains yet to be fully understood. This project works at the intersection of dynamical modelling, statistical signal processing, statistical
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Methods of balancing model complexity with goodness of fit include Akaike's information criterion (AIC), Schwarz's Bayesian information criterion (BIC), minimum description length (MDL) and minimum
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based on matched-filter statistics. Detecting the unknown relies on the development of complex algorithms at the forefront of statistics, machine learning, and data science. This multi-disciplinary
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: 10.1093/comjnl/bxm117 D. L. Dowe (2011a), "MML, hybrid Bayesian network graphical models, statistical consistency, invariance and uniqueness ", Handbook of the Philosophy of Science - (HPS Volume 7
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Conversational Tactile Map for Blind People. In SIGACCESS2019, pages 682–684, 2019. E. Fast et al.˙ Iris: A Conversational Agent for Complex Tasks. In CHI2018, pages 1–12. ACM, 2018. Y. Yang, K. Marriott, M