17 citations · 17 across the 3 of their papers we have counts for
6 papers
Transversal Pooling Neural Networks
Emily J. King, Dustin G. Mixon, Michael Perlmutter +1
Many learning tasks require stability to small transformations while retaining sensitivity to larger ones. We introduce \emph{transversal pooling neural networks}, which generalize…
Persistent Homology for Labeled Datasets: Gromov-Hausdorff Stability and Generalized Landscapes
Yaoying Fu, Evgeniya Lagoda, Shiying Li +3
Techniques from metric geometry have become fundamental tools in modern mathematical data science, providing principled methods for comparing datasets modeled as finite metric spac…
Using machine learning to downscale coarse-resolution environmental variables for understanding the spatial frequency of convective storms
Hungjui Yu, Lander Ver Hoef, Kristen L. Rasmussen +1
Global climate models (GCMs), typically run at ~100-km resolution, capture large-scale environmental conditions but cannot resolve convection and cloud processes at kilometer scale…
Knowledge-Guided Machine Learning: Illustrating the use of Explainable Boosting Machines to Identify Overshooting Tops in Satellite Imagery
Nathan Mitchell, Lander Ver Hoef, Imme Ebert-Uphoff +4
Machine learning (ML) algorithms have emerged in many meteorological applications. However, these algorithms struggle to extrapolate beyond the data they were trained on, i.e., the…
How to use score-based diffusion in earth system science: A satellite nowcasting example
Randy J. Chase, Katherine Haynes, Lander Ver Hoef +1
Machine learning (ML) is used for many earth science applications; however, traditional ML methods trained with squared errors often create blurry forecasts. Diffusion models are a…
A Primer on Topological Data Analysis to Support Image Analysis Tasks in Environmental Science
Lander Ver Hoef, Henry Adams, Emily J. King +1
Topological data analysis (TDA) is a tool from data science and mathematics that is beginning to make waves in environmental science. In this work, we seek to provide an intuitive…