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Found 3 papers, 0 papers with code
Modeling Smooth Backgrounds and Generic Localized Signals with Gaussian Processes
We demonstrate the application of this approach to modeling the background to searches for dijet resonances at the Large Hadron Collider and describe how the approach can be used in the search for generic localized signals.
Data Analysis, Statistics and Probability High Energy Physics - Experiment High Energy Physics - Phenomenology
Bayesian Inference on Matrix Manifolds for Linear Dimensionality Reduction
We reframe linear dimensionality reduction as a problem of Bayesian inference on matrix manifolds.
Dependent Matérn Processes for Multivariate Time Series
For the challenging task of modeling multivariate time series, we propose a new class of models that use dependent Mat\'ern processes to capture the underlying structure of data, explain their interdependencies, and predict their unknown values.
