Search Results for author:
Found 6 papers, 0 papers with code
Spatio-Temporal Surrogates for Interaction of a Jet with High Explosives: Part II -- Clustering Extremely High-Dimensional Grid-Based Data
We show how we can use the randomness of both the random projections, and the choice of initial centroids in k-means clustering, to determine the number of clusters in our data set.
Spatio-Temporal Surrogates for Interaction of a Jet with High Explosives: Part I -- Analysis with a Small Sample Size
The characteristics of our data set are unique - the vector-valued outputs from each simulation are available at over two million spatial locations; each simulation is run for a relatively small number of time steps; the size of the computational domain varies with each simulation; and resource constraints limit the number of simulations we can run.
Data Mining for Faster, Interpretable Solutions to Inverse Problems: A Case Study Using Additive Manufacturing
Solving inverse problems, where we find the input values that result in desired values of outputs, can be challenging.
Intelligent sampling for surrogate modeling, hyperparameter optimization, and data analysis
Sampling techniques are used in many fields, including design of experiments, image processing, and graphics.
Classification of Orbits in Poincaré Maps using Machine Learning
Poincar\'e plots, also called Poincar\'e maps, are used by plasma physicists to understand the behavior of magnetically confined plasma in numerical simulations of a tokamak.
Randomized Algorithms for Scientific Computing (RASC)
Randomized algorithms have propelled advances in artificial intelligence and represent a foundational research area in advancing AI for Science.
