186 citations · 436 across the 10 of their papers we have counts for
11 papers
The High Explosives and Affected Targets (HEAT) Dataset
Bryan Kaiser, Kyle Hickmann, Sharmistha Chakrabarti +6
Artificial Intelligence (AI) surrogate models provide a computationally efficient alternative to full-physics simulations, but no public datasets currently exist for training and v…
Out-of-distribution transfer of PDE foundation models to material dynamics under extreme loading
Mahindra Rautela, Alexander Most, Siddharth Mansingh +9
Most PDE foundation models are pretrained and fine-tuned on fluid-centric benchmarks. Their utility under extreme-loading material dynamics remains unclear. We benchmark out-of-dis…
Particle image velocimetry analysis with simultaneous uncertainty quantification using Bayesian neural networks
Mia Morrell, Kyle Hickmann, Brandon Wilson
Particle image velocimetry (PIV) is an effective tool in experimental fluid mechanics to extract flow fields from images. Recently, convolutional neural networks (CNNs) have been u…
Optimal Bounds on Nonlinear Partial Differential Equations in Model Certification, Validation, and Experimental Design
M. McKerns, F. J. Alexander, K. S. Hickmann +2
We demonstrate that the recently developed Optimal Uncertainty Quantification (OUQ) theory, combined with recent software enabling fast global solutions of constrained non-convex o…
A Multiresolution Ensemble Kalman Filter using Wavelet Decomposition
Kyle S. Hickmann, Humberto C. Godinez
We present a method of using classical wavelet based multiresolution analysis to separate scales in model and observations during data assimilation with the ensemble Kalman filter.…
Quantifying Uncertainty in Stochastic Models with Parametric Variability
Kyle S. Hickmann, James M. Hyman, Sara Y. Del Valle
We present a method to quantify uncertainty in the predictions made by simulations of mathematical models that can be applied to a broad class of stochastic, discrete, and differen…
Forecasting the 2013--2014 Influenza Season using Wikipedia
Kyle S. Hickmann, Geoffrey Fairchild, Reid Priedhorsky +4
Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy…
Advancements in the ADAPT Photospheric Flux Transport Model
Kyle S. Hickmann, Humberto C. Godinez, Carl J. Henney +1
Global maps of the solar photospheric magnetic flux are fundamental drivers for simulations of the corona and solar wind and therefore are important predictors of geoeffective even…
A network-patch methodology for adapting agent-based models for directly transmitted disease to mosquito-borne disease
Carrie A. Manore, Kyle S. Hickmann, James M. Hyman +4
Mosquito-borne diseases cause significant public health burden, mostly in tropical and sub-tropical regions, and are widely emerging or re-emerging in areas where previously absent…
Path-Based Distance for Street Map Comparison
Mahmuda Ahmed, Brittany Terese Fasy, Kyle S. Hickmann +1
Comparing two geometric graphs embedded in space is important in the field of transportation network analysis. Given street maps of the same city collected from different sources,…
Transmission eigenvalues and thermoacoustic tomography
David Finch, Kyle S. Hickmann
The spectrum of the interior transmission problem is related to the unique determination of the acoustic properties of a body in thermoacoustic imaging. Under a non-trapping hypoth…