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models for high-dimensional and functional data ”, led by Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available
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“Bayesian Rank-based unsupervised Integration of multi-source Data in cancer Genomics and the digital Economy (BRIDGE)”, funded in 2025 by the Research Council of Norway (RCN) under the open scheme
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sources, and account for uncertainty in ways that are relevant to real-world management. At the same time, it addresses how models are used in practice clarifying the assumptions they carry, how
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incomplete data sources, and account for uncertainty in ways that are relevant to real-world management. At the same time, it addresses how models are used in practice clarifying the assumptions they carry
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the theory and supports perceptual studies. This includes: contributing to method development on rhythm modeling; performing source separation on commercial recordings and extracting audio features (onsets