3 citations · 9 across the 11 of their papers we have counts for
5 papers · 1 filter
Learning vertical coordinates via automatic differentiation of a dynamical core
Tim Whittaker, Seth Taylor, Elsa Cardoso-Bihlo +2
Terrain-following coordinates in atmospheric models often imprint their grid structure onto the solution, particularly over steep topography, where distorted coordinate layers can…
Diffeomorphic Neural Operator Learning
Seth Taylor, Alex Bihlo, Jean-Christophe Nave
We present an operator learning approach for a class of evolution operators using a composition of a learned lift into the space of diffeomorphisms of the domain and the group acti…
Low-rank adaptive physics-informed HyperDeepONets for solving differential equations
Etienne Zeudong, Elsa Cardoso-Bihlo, Alex Bihlo
HyperDeepONets were introduced in Lee, Cho and Hwang [ICLR, 2023] as an alternative architecture for operator learning, in which a hypernetwork generates the weights for the trunk…
ForeCite: Adapting Pre-Trained Language Models to Predict Future Citation Rates of Academic Papers
Gavin Hull, Alex Bihlo
Predicting the future citation rates of academic papers is an important step toward the automation of research evaluation and the acceleration of scientific progress. We present $\…
Mapping Galaxy Images Across Ultraviolet, Visible and Infrared Bands Using Generative Deep Learning
Youssef Zaazou, Alex Bihlo, Terrence S. Tricco
We demonstrate that generative deep learning can translate galaxy observations across ultraviolet, visible, and infrared photometric bands. Leveraging mock observations from the Il…