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Neural Likelihood Approximation for Integer Valued Time Series Data
Stochastic processes defined on integer valued state spaces are popular within the physical and biological sciences.
Computation of random time-shift distributions for stochastic population models
Even in large systems, the effect of noise arising from when populations are initially small can persist to be measurable on the macroscale.
Model and Data Reduction for Data Assimilation: Particle Filters Employing Projected Forecasts and Data with Application to a Shallow Water Model
The understanding of nonlinear, high dimensional flows, e. g, atmospheric and ocean flows, is critical to address the impacts of global climate change.
Dimensionality Reduction
Dynamical Systems
Optimization and Control
Chaotic Dynamics
Atmospheric and Oceanic Physics
Data Analysis, Statistics and Probability
65C20, 62-08, 86-08, 62M20
