3 citations · 4 across the 5 of their papers we have counts for
5 papers
Extending Neural Operators: Robust Handling of Functions Beyond the Training Set
Blaine Quackenbush, Paul J. Atzberger
We develop a rigorous framework for extending neural operators to handle out-of-distribution input functions. We leverage kernel approximation techniques and provide theory for cha…
Transferable Foundation Models for Geometric Tasks on Point Cloud Representations: Geometric Neural Operators
Blaine Quackenbush, Paul J. Atzberger
We introduce methods for obtaining pretrained Geometric Neural Operators (GNPs) that can serve as basal foundation models for use in obtaining geometric features. These can be used…
Geometric Neural Operators (GNPs) for Data-Driven Deep Learning of Non-Euclidean Operators
Blaine Quackenbush, Paul J. Atzberger
We introduce Geometric Neural Operators (GNPs) for accounting for geometric contributions in data-driven deep learning of operators. We show how GNPs can be used (i) to estimate ge…
Periodic intermediate -expansions of Pisot numbers
Blaine Quackenbush, Tony Samuel, Matthew A. West
The subshift of finite type property (also known as the Markov property) is ubiquitous in dynamical systems and the simplest and most widely studied class of dynamical systems are…
On the continuity of entropy of Lorenz maps
Zoe Cooperband, Erin P. J. Pearse, Blaine Quackenbush +3
We consider a one parameter family of Lorenz maps indexed by their point of discontinuity and constructed from a pair of bilipschitz functions. We prove that their topological…