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Solving large complex partial differential equations (PDEs), such as those that arise in computational fluid dynamics (CFD), is a computationally expensive process.
Graph Element Networks: adaptive, structured computation and memory
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Prediction of Aerodynamic Flow Fields Using Convolutional Neural Networks
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Aerodynamic design via control theory
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Adam: A method for stochastic optimization
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Development of a consistent discrete adjoint solver in an evolving aerodynamic design framework
Albring, T., Sagebaum, M., and Gauger, N. R · 2015
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Efficient aerodynamic design using the discrete adjoint method in SU2
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Convolutional neural networks on graphs with fast localized spectral filtering
Defferrard, M., Bresson, X., and Vandergheynst, P · 2016
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Economon, T. D., Palacios, F., Copeland, S. R., Lukaczyk, T. W., and Alonso, J. J · 2016
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Convolutional neural networks for steady flow approximation
Guo, X., Li, W., and Iorio, F · 2016
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Semi-supervised classification with graph convolutional networks
Kipf, T. N. and Welling, M · 2016
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Geometric deep learning: going beyond euclidean data
Bronstein, M. M., Bruna, J., LeCun, Y., Szlam, A., and Vandergheynst, P · 2017
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Inductive representation learning on large graphs
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Deep Fluids: A Generative Network for Parameterized Fluid Simulations
Kim, B., Azevedo, V. C., Thuerey, N., Kim, T., Gross, M., and Solenthaler, B · 2018
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From Deep to Physics-Informed Learning of Turbulence: Diagnostics
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SPNets: Differentiable Fluid Dynamics for Deep Neural Networks
Schenck, C. and Fox, D · 2018
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Latent-space Physics: Towards Learning the Temporal Evolution of Fluid Flow
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Hamilton, W., Ying, Z., and Leskovec, J · 2017
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Qi, C. R., Yi, L., Su, H., and Guibas, L. J · 2017
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Augmentation of Turbulence Models Using Field Inversion and Machine Learning
Singh, A. P., Duraisamy, K., and Zhang, Z. J · 2017
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Unsteady continuous adjoint approach for aerodynamic design on dynamic meshes
Economon, T. D., Palacios, F., and Alonso, J. J
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SU2: An Open-Source Suite for Multiphysics Simulation and Design
Economon, T. D., Palacios, F., Copeland, S. R., Lukaczyk, T. W., and Alonso, J. J
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Wiewel, S., Becher, M., and Thuerey, N · 2018
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Turbulence Modeling in the Age of Data
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