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headlines around the world when a “work of art created by an algorithm” was sold at auction by Christie’s for $432,500 – nearly 45 times the value estimated before auction. It turned out that the group behind
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develop individual-based models (also called agent-based models) to simulate insect-plant interactions. These are computer simulations where each individual animal is simulated in detail within a virtual
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systems are based on the Cassowary algorithm , developed in part by Monash researchers. While constraint-based layout is powerful, it can be difficult for users to understand the interactions and behaviour
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data infrastructure necessary for collaborative research into, and development of, analytical techniques and algorithmic models. The Faculty of Information Technology has a mission to advance social good
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science conference [1]; one of our papers is recognised as Clarivate Web of Science HighCite (top 1% of papers for the field of research) [2]; three of our algorithms (TS-Chief, InceptionTime and Rocket
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Education, undoubtedly, is one of the most fundamental means for people to gain personal and professional development. Given its importance, both researchers and practitioners have endeavored
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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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feasibility, and to facilitate the rapid translation of study findings into registry practice and health data environments. Project goals: The aim of the project is to develop cutting-edge AI algorithms
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achieve what neither a human being nor a machine can achieve on their own.The aim of this research is to develop cutting-edge Human-in-the-Loop Machine Learning algorithms that are able to avoid bias
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This project will investigate and develop the ways in which AI algorithms and practices can be made transparent and explainable for use in law enforcement and judicial applications The Faculty