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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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Project description: Nowadays, data-driven machine learning algorithms are well suited to solve real-world problems that require high-level prediction accuracy. However, it seems as if nothing beats
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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
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will provide new models and algorithms for energy-transport integration, advancing the knowledge of mitigation strategies for sustainable urban development. #sustainability PhD student role description
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The existing deep learning based time series classification (TSC) algorithms have some success in multivariate time series, their accuracy is not high when we apply them on brain EEG time series (65
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-readable representations, such as distributed representations of text augmented with random noises [1] or unnatural text curated by replacing sensitive tokens with random non-sensitive ones [2]. First, such