346 citations · 706 across the 5 of their papers we have counts for
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cs.LG2020★ 189 cited
Transformers for Modeling Physical Systems
Nicholas Geneva, Nicholas Zabaras
Transformers are widely used in natural language processing due to their ability to model longer-term dependencies in text. Although these models achieve state-of-the-art performan…
physics.comp-ph2020★ 36 cited
Multi-fidelity Generative Deep Learning Turbulent Flows
Nicholas Geneva, Nicholas Zabaras
In computational fluid dynamics, there is an inevitable trade off between accuracy and computational cost. In this work, a novel multi-fidelity deep generative model is introduced…