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Dimension reduction for stochastic dynamical systems forced onto a manifold by large drift
Systems composed of large numbers of interacting agents often admit an effective coarse-grained description in terms of a multidimensional stochastic dynamical system, driven by small-amplitude intrinsic noise. In...
dimension reduction Dynamical systems Stochastic Processes timescale separation /dk/atira/pure/subjectarea/asjc/3100/3109 name=Statistical and Nonlinear Physics /dk/atira/pure/subjectarea/asjc/2600/2613 name=Statistics and Probability /dk/atira/pure/subjectarea/asjc/2600/2611 name=Modelling and Simulation /dk/atira/pure/subjectarea/asjc/2600/2610 name=Mathematical Physics /dk/atira/pure/subjectarea/asjc/3100/3100 name=General Physics and Astronomy
Dimension reduction for stochastic dynamical systems forced onto a manifold by large drift
Systems composed of large numbers of interacting agents often admit an effective coarse-grained description in terms of a multidimensional stochastic dynamical system, driven by small-amplitude intrinsic noise. In...
dimension reduction Dynamical systems Stochastic Processes timescale separation /dk/atira/pure/subjectarea/asjc/3100/3109 name=Statistical and Nonlinear Physics /dk/atira/pure/subjectarea/asjc/2600/2613 name=Statistics and Probability /dk/atira/pure/subjectarea/asjc/2600/2611 name=Modelling and Simulation /dk/atira/pure/subjectarea/asjc/2600/2610 name=Mathematical Physics /dk/atira/pure/subjectarea/asjc/3100/3100 name=General Physics and Astronomy
High-dimensional change point estimation via sparse projection
Changepoints are a very common feature of Big Data that arrive in the form of a data stream. In this paper, we study high-dimensional time series in which, at certain time points, the mean structure changes in a sparse subset...
Disentangling the effects of traits with shared clustered genetic predictors using multivariable Mendelian randomization.
When genetic variants in a gene cluster are associated with a disease outcome, the causal pathway from the variants to the outcome can be difficult to disentangle. For example, the chemokine receptor gene cluster contains...
Exploratory factor analysis with structured residuals for brain network data.
Dimension reduction is widely used and often necessary to make network analyses and their interpretation tractable by reducing high-dimensional data to a small number of underlying variables. Techniques such as exploratory...