Machine Learning
A tensor provides a concise way to codify the interdependence of complex data. Treating a tensor as a d-way array, each entry records the interaction between the different indices. Clustering provides a way to parse the complexity of the data into …
Rapid progress in machine learning (ML) has engendered numerous applications across the sciences. Deployment of modern ML systems have increased our ability to validate and automate the scientific process, broadening the space for discovery. However, …
A tensor provides a concise way to codify the interdependence of complex data. Treating a tensor as a d-way array, each entry records the interaction between the different indices. Clustering provides a way to parse the complexity of the data into …
The Earth's climate is a complex system of micro and macroscopic interdependencies. Classifying the surface of The Earth into climate biomes is a way to parse this information down to provide meaningful diagnostics to relate the physical and …
This work aims to determine climate biomes directly from data, determine where they are changing, and assign a value of trust to our classification.
The goal of this work is to discover and analyze climatic signatures within E3SM MPAS-O data of the Southern Ocean.
In this work, we attempt to understand the mathematical connections between different types of tensor factorizations.