When computational constraints prohibit model evaluation at all but a small number of parameter settings, a dimension-reduced emulator of the system can be constructed and interrogated at arbitrary parameter regimes. Existing approaches to emulation consider models with deterministic output. However, in many cases the underlying mathematical mod...
Creator:
Chkrebtii, Oksana (The Ohio State University)
Created:
2018-04-24
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Hydrological forecasts strongly rely on predictions of precipitation amounts as meteorological inputs to hydrological models. Ensemble weather predictions provide a number of different scenarios that reflect the uncertainty about these meteorological inputs, but are often biased and underdispersive, and therefore require statistical postprocessi...
Creator:
Scheuerer, Michael (National Oceanographic and Atmospheric Administration (NOAA))
Created:
2018-04-24
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Consider observing a collection of discrete events within a network that reflects how network nodes influence one another. Such data are common in spike trains recorded from biological neural networks, interactions within a social network, and a variety of other settings. Data of this form may be modeled as self-exciting point processes, in whic...
Creator:
Willett, Rebecca (University of Wisconsin, Madison)
Created:
2018-04-24
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
The maximum association between two multivariate variables X and Y is defined as the maximal value that a bivariate ssociation measure between one-dimensional projections a'X and b'Y can attain. Taking the Pearson correlation as projection index results in the first canonical correlation coefficient. We propose to use more robust association mea...
Creator:
Filzmoser, Peter (Technische Universität Wien)
Created:
2018-04-24
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Hawkes processes has been a popular point process model for capturing mutual excitation of discrete events. In the network setting, this can capture the mutual influence between nodes, which has a wide range of applications in neural science, social networks, and crime data analysis. In this talk, I will present a statistical change-point detect...
Creator:
Xie, Yao (Georgia Institute of Technology)
Created:
2018-04-24
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Convex matrix optimization problems with low-rank solutions play a fundamental role in signal processing, statistics, and related disciplines. These problems are difficult to solve because of the cost of maintaining the matrix decision variable, even though the low-rank solution has few degrees of freedom. This talk presents an algorithm that pr...
Creator:
Tropp, Joel (California Institute of Technology)
Created:
2018-04-24
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Drifters are freely-drifting satellite-tracked instruments deployed in our oceans to better understand oceanic currents and circulation. In this talk we present a stochastic spatiotemporal model which describes the trajectories that drifters follow. The modelling challenge is that data moves in both time and space, referred to as a "Lagrangian" ...
Creator:
Sykulski, Adam (University of Lancaster)
Created:
2018-04-24
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
We propose a fully spatiotemporal approach for identifying spatially varying modes of oscillationin fluid dynamics simulation output by means of multitaper frequency wavenumber spectral analysis. Two-dimensional frequency wavenumber spectral analysis allows one to decompose waveforms into standing or traveling variety. The extended higher-dimens...
Creator:
Haley, Charlotte (Argonne National Laboratory)
Created:
2018-04-24
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.