Ravi G. Patel

Orcid: 0000-0002-2779-3739

Affiliations:
  • Sandia National Laboratories, Center for Computing Research, Albuquerque, NM, USA
  • Cornell University, Sibley School of Mechanical and Aerospace Engineering, Ithaca, NY, USA


According to our database1, Ravi G. Patel authored at least 13 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response.
CoRR, 2024

Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes.
CoRR, 2024

2022
Thermodynamically consistent physics-informed neural networks for hyperbolic systems.
J. Comput. Phys., 2022

Error-in-variables modelling for operator learning.
Proceedings of the Mathematical and Scientific Machine Learning, 2022

2021
Reduced Basis Approximations of Parameterized Dynamical Partial Differential Equations via Neural Networks.
CoRR, 2021

A Block Coordinate Descent Optimizer for Classification Problems Exploiting Convexity.
Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

Partition of Unity Networks: Deep HP-Approximation.
Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

2020
A physics-informed operator regression framework for extracting data-driven continuum models.
CoRR, 2020

Robust Training and Initialization of Deep Neural Networks: An Adaptive Basis Viewpoint.
Proceedings of Mathematical and Scientific Machine Learning, 2020

GMLS-Nets: A Machine Learning Framework for Unstructured Data.
Proceedings of the AAAI 2020 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 23rd - to, 2020

2019
Three-dimensional conditional hyperbolic quadrature method of moments.
J. Comput. Phys. X, 2019

GMLS-Nets: A framework for learning from unstructured data.
CoRR, 2019

2018
Nonlinear integro-differential operator regression with neural networks.
CoRR, 2018


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