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Gaussian Process Regression Generalizes Linear PDE Solvers“, Apr. 2024, Preprint, https://arxiv.org/abs/2212.12474
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efficient simulators for continuous and discrete variable systems with noise based on Gaussian/stabilizer decompositions quantum error mitigation and correction for continuous variable systems evaluating and
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. Gaussian Process Regression) model to describe the relationship between process parameters and material properties will be developed and subsequently exposed to Bayesian optimization to find the optimal set
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on Gaussian/stabilizer decompositions quantum error mitigation and correction for continuous variable systems evaluating and rigorously define the computational power of continuous variable systems Your Profile
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image sequences. As a benchmark, end-to-end deep learning models will be developed using raw image data. In parallel, shallow learning models (e.g., Gaussian processes) will be explored based on insights