Search for dissertations about: "cluster models"
Showing result 21 - 25 of 203 swedish dissertations containing the words cluster models.
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21. From experiments with images to 3D models
Abstract : For developing the next generation sustainable materials, it is often crucial to understand and control their properties and function. This work presents cross-disciplinary research starting with experimentally fabricated porous soft biomaterials and images of their micro-structure obtained by electron or laser microscopy. READ MORE
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22. Topics on Generative Models in Machine Learning
Abstract : Latent variable models have been extensively studied within the field of machine learning in recent years. Especially in combination with neural networks and training through back propagation, they have proven successful for a variety of tasks; notably sample gener- ation, clustering, disentanglement and interpolation. READ MORE
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23. Geometrical and percolative properties of spatially correlated models
Abstract : This thesis consists of four papers dealing with phase transitions in various models of continuum percolation. These models exhibit complicated dependencies and are generated by different Poisson processes. For each such process there is a parameter, known as the intensity, governing its behavior. READ MORE
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24. Gene expression profiling in animal models of alcoholism
Abstract : Genetic and environmental factors in alcoholism interact at the level of the transcriptome to encode the phenotypic traits of this complex clinical syndrome. Because of this, the prospect of simultaneous, genome wide, high-throughput analysis of gene expression in key brain areas potentially offers a novel strategy to identify new molecular treatment targets in this disease. READ MORE
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25. Charged particle distributions and robustness of the neural network pixel clustering in ATLAS
Abstract : This thesis contains a study of the robustness of the artificial neural network used in the ATLAS track reconstruction algorithm as a tool to recover tracks in dense environments. Different variations, motivated by potential discrepancies between data and simulation, are performed to the neural network’s input while monitoring the corresponding change in the output. READ MORE