research
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04/06/2023
Neural Operator Learning for Ultrasound Tomography Inversion
Neural operator learning as a means of mapping between complex function ...
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02/28/2023
A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions
Physics-informed neural networks (PINNs) as a means of solving partial d...
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02/02/2023
Deep neural operators can serve as accurate surrogates for shape optimization: A case study for airfoils
Deep neural operators, such as DeepONets, have changed the paradigm in h...
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10/23/2022
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks
Physics-informed neural networks (PINNs) are emerging as popular mesh-fr...
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10/26/2021
Physics-Informed Neural Networks (PINNs) for Parameterized PDEs: A Metalearning Approach
Physics-informed neural networks (PINNs) as a means of discretizing part...
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06/25/2021
