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This PhD project is funded by a successful ARC Discovery Project grant: "Improving human reasoning with causal Bayesian networks: a user-centric, multimodal, interactive approach" and the successful
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plants they visit and pollinate. Bayesian networks (BNs), and other probabilistic graphical models, can provide a visual representation of the underlying structure of a complex system by representing
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estimation methods for deep neural networks. A principled Bayesian framework for multimodal uncertainty modeling. Robust learning algorithms under missing modalities and distribution shifts. New uncertainty
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networks, Bayesian inference, computational neuroscience, mathematics.
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. This project concerns creating suitable models - and/or general hybrid models - as yet undeveloped. References: Comley, Joshua W. and D.L. Dowe (2003). General Bayesian Networks and Asymmetric Languages, Proc
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/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) Philosophy
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has been identified References: Comley, Joshua W. and D.L. Dowe (2003). General Bayesian Networks and Asymmetric Languages, Proc. 2nd Hawaii International Conference on Statistics and Related Fields, 5
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) [Christopher Stewart WALLACE (1933-2004) memorial special issue [and front cover and back cover]], pp523-560 (and here). www.doi.org: 10.1093/comjnl/bxm117 D. L. Dowe (2011a), "MML, hybrid Bayesian network
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. Butler, C. Goncu, and L. Holloway. Tactile presentation of network data: Text, matrix or diagram? In CHI2020, pages 1–12, 2020. I. Zukerman et al.˙Exploratory Interaction with a Bayesian Argumentation
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The Opportunity Monash University is seeking a Project Manager to play a central role in the delivery of the MRFF funded PANTHER Trial (Precision medicine Adaptive Network Platform Trial in Hypoxemic acute