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the different actors' beliefs and intentions. We will study the properties of such explanations, present algorithms for automatically computing them as well as extensions to existing frameworks and evaluate
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that occurs within these biological neural networks, so that these networks can be leveraged for AI applications. In addition, you will develop mathematical and computational neuroscience models
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operators for these notions. Over the past fifty years, such non-classical logics have proved vital in computer science and logic-based artificial intelligence: after all, any intelligent agent must be able
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with industry in order to develop professional practice skills Program dates: 22 June to 31 July (6 weeks) and 30 Nov to 12 Feb 2027 (9 weeks and excludes 2 week shut down period) About the opportunity
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methods dealing with model complexity - e.g., AIC, BIC, MDL, MML - can enhance deep learning. References: D. L. Dowe (2008a), "Foreword re C. S. Wallace", Computer Journal, Vol. 51, No. 5 (Sept. 2008
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. Required knowledge Strong background in machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch
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., Pan, S., Aggarwal, C., & Salehi, M. (2022). Deep learning for time series anomaly detection: A survey. ACM Computing Surveys.
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Northern Territory Medical Program, Paramedicine, Rural Clinical School, and the University Department of Rural Health. Our postgraduate education pathways (Remote Health Practice program), provides
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of health and medical research. WAHTN is an accredited NHMRC Research Translation Centre and a member of the Australian Health Research Alliance (AHRA). The Consumer and Community Involvement Program (CCI
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Areas covered include wireless communications; intelligent monitoring and surveillance for natural and industrial environments; intelligent embedded systems; decision making and machine learning; wireless sensor networks; green communications; next generation wireless broadband networks; signal...