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The world is dynamic, in constant flux. However, machine learning typically learns static models from historical data. As the world changes, these models decline in performance, sometimes catastrophically so. This PhD will develop technologies for addressing this serious problem, building upon...
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This project heavily focuses on maps (e.g. GoogleMaps or Open Street Map). We will explore various properties of road networks, including the granularity of road networks, routes and trajectories on road networks, and query processing on road networks. A number of inter-disciplinary...
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Monash's competitive scholarship selection process requirements ; and meet Monash English language proficiency requirements . This scholarship is also available to students undertaking Joint Research Awards
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Insects are vital components of natural and agricultural ecosystems that interact with plants in complex ways. Computer simulations can help us understand these interactions to improve crop
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wouldn't be possible. Am I eligible? You must be one of the following: An Australian citizen You must meet the following criteria: Commencing full-time studies in a Monash Enabling program/Monash Transition
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) McCormack J. (2017) Niche Constructing Drawing Robots . In: Correia J., Ciesielski V., Liapis A. (eds) Computational Intelligence in Music, Sound, Art and Design. EvoMUSART 2017. Boden, M. Creativity and Art
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I supervise computational projects in electron microscopy imaging for investigating materials at atomic resolution. Some projects centre on analysing experimental data acquired by experimental
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analytical imaging methods, then working with collaborators to apply these methods to biomedical research, diagnostic imaging and beyond. Research projects vary from purely theoretical, to computational
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testing approaches that can be used to verify that machine learning models are not biased. Required knowledge Software engineering, software testing, statistics, machine learning
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Yuan-Fang Li Derry Wijaya Mohammed Eunus Ali Research area Vision and Language While large multimodal models (LMMs) have obtained strong performance on many multi-modal tasks, they may still hallucinate