4 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…
Protein Drift-Diffusion in Membranes with Non-equilibrium Fluctuations arising from Gradients in Concentration or Temperature
D. Jasuja, P. J. Atzberger
We investigate proteins within heterogeneous cell membranes where non-equilibrium phenomena arises from spatial variations in concentration and temperature. We develop simulation m…
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…
Sparse -Autoencoders for Scientific Data Compression
Matthias Chung, Rick Archibald, Paul Atzberger +1
Scientific datasets present unique challenges for machine learning-driven compression methods, including more stringent requirements on accuracy and mitigation of potential invalid…