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Aerodynamic shape optimization has many industrial applications.
The characteristics of 78 related airfoil sections from tests in the variable density wind tunnel
Jacobs, Eastmann N., Ward, Kenneth E., and Pinkerton, Robert M · 1948
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Use of the Boltzmann Equation to Simulate Lattice-gas Automata
McNamara, G. and Zanetti, G · 1988
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XFOIL: An Analysis and Design System for Low Reynolds Number Airfoils
Drela, M · 1989
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Multitask Learning
Caruana, R · 1997
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Polycube-maps
Tarini, M., Hormann, K., Cignoni, P., and Montani, C · 2004
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Efficient optimization design method using kriging model
Jeong, Shinkyu, Murayama, Mitsuhiro, and Yamamoto, Kazuomi · 2005
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The Curse of Highly Variable Functions for Local Kernel Machines
Bengio, Y., Delalleau, O., and Roux, N. Le · 2006
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Gaussian Process for Machine Learning
Rasmussen, C. E. and Williams, C. K · 2006
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Review of Utilization of Genetic Algorithms in Heat Transfer Problems
Gosselin, L., Tye-Gingras, M., and Mathieu-Potvin, F · 2009
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Numerical Models for Differential Problems , volume 2
Quarteroni, A. and Quarteroni, S · 2009
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Shape Optimization of Arch Dams by Metaheuristics and Neural Networks for Frequency Constraints
Gholizadeh, S. and Seyedpoor, S.M · 2011
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All-hex mesh generation via volumetric polycube deformation
Gregson, James, Sheffer, Alla, and Zhang, Eugene · 2011
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ANSYS FLUENT Theory Guide
Inc., Ansys · 2011
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Efficient multipoint aerodynamic design optimization via cokriging
Toal, David JJ and Keane, Andy J · 2011
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Multi-GPU Performance of Incompressible Flow Computation by Lattice Boltzmann Method on GPU Cluster
Xian, W. and Takayuki, A · 2011
Cited alongside, same era.
State of the art in quad meshing
Bommes, D., Lvy, B., Pietroni, N., Puppo, E., a, C. Silv, Tarini, M., and Zorin, D · 2012
Cited alongside, same era.
Disentangling factors of variation for facial expression recognition
Rifai, Salah, Bengio, Yoshua, Courville, Aaron, Vincent, Pascal, and Mirza, Mehdi · 2012
Cited alongside, same era.
Quad-mesh generation and processing: A survey
Bommes, David, Lévy, Bruno, Pietroni, Nico, Puppo, Enrico, Silva, Claudio, Tarini, Marco, and Zorin, Denis · 2013
Cited alongside, same era.
Response surface methods for efficient aerodynamic surrogate models
Rosenbaum, Benjamin and Schulz, Volker · 2013
Cited alongside, same era.
Surrogate Models for Aerodynamic Shape Optimization , pp. 285–312
Ulaganathan, S. and Asproulis, N · 2013
Convolutional Neural Networks for Steady Flow Approximation
Guo, X., Li, W., and Iorio, F · 2016
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Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., and Sun, J · 2016
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Semi-supervised classification with graph convolutional networks
Kipf, Thomas N and Welling, Max · 2016
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Geometric deep learning on graphs and manifolds using mixture model cnns
Monti, Federico, Boscaini, Davide, Masci, Jonathan, Rodolà, Emanuele, Svoboda, Jan, and Bronstein, Michael M · 2016
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Template-Based Monocular 3D Shape Recovery Using Laplacian Meshes
Ngo, D., Ostlund, J., and Fua, P · 2016
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Cited alongside, same era.
A Review of Adjoint Methods for Sensitivity Analysis, Uncertainty Quantification and Optimization in Numerical Codes
Allaire, G · 2015
Cited alongside, same era.
Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., and Yuille, A · 2015
Cited alongside, same era.
Adam: A Method for Stochastic Optimisation
Kingma, D.P. and Ba, J · 2015
Cited alongside, same era.
Automated Aerodynamic Vehicle Shape Optimization Using Neural Networks and Evolutionary Optimization
Lundberg, A., Hamlin, P., Shankar, D., Broniewicz, A., Walker, T., and Landstram, C · 2015
Cited alongside, same era.
Toward the Coevolution of Novel Vertical-Axis Wind Turbines
Preen, R. J. and Bull, L · 2015
Cited alongside, same era.
Massively multitask networks for drug discovery
Ramsundar, Bharath, Kearnes, Steven M., Riley, Patrick, Webster, Dale, Konerding, David E., and Pande, Vijay S · 2015
Cited alongside, same era.
Comparison of Shape Optimization Techniques Coupled with Genetic Algorithms for a Wind Turbine Airfoil
Orman, E. and Durmus, G · 2016
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Accelerating Eulerian Fluid Simulation With Convolutional Networks
Tompson, J., Schlachter, K., Sprechmann, P., and Perlin, K · 2016
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Multi-Scale Context Aggregation by Dilated Convolutions
Yu, F. and Koltun, V · 2016
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Gaussian process for aerodynamic pressures prediction in fast fluid structure interaction simulations
Chiplunkar, Ankit, Bosco, Elisa, and Morlier, Joseph · 2017
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Automatic Differentiation Dased Discrete Adjoint Method for Aerodynamic Design Optimization on Unstructured Meshes
Gao, Yisheng, Wu, Yizhao, and Xia, Jian · 2017
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Characterization of the effects of manufacturing geometry details on exhaust flow noise using lattice boltzmann based method simulations
Nardari, C., Mann, A., and Schindele, T · 2017
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Multi-objective aerodynamic optimization of the streamlined shape of high-speed trains based on the kriging model
Xu, Gang, Liang, Xifeng, Yao, Shuanbao, Chen, Dawei, and Li, Zhiwei · 2017
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State-of-the-art in aerodynamic shape optimisation methods
Skinner, S.N. and Zare-Behtash, H · 2018
Closest in time.