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the Department of Physics. Machine learning has made enormous progress during recent years, entering almost all spheres of technology, economy and our everyday life. Machines perform comparably to, or even surpass
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and Sobolev-type spaces (with Hytönen and/or Korte), Conformal deformations of metric measure spaces and/or general regularity and convergence for graph-based machine learning using stochastic game
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to model and simulate building energy systems. Use of machine learning techniques to forecast cooling demand. Proven ability to analyse complex information, including large datasets, and summarise
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