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Aerodynamic Performance Prediction of Airfoils with Transformers

https://doi.org/10.2139/ssrn.5370691
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A deep learning approach for efficiently and accurately evaluating the flow field of supercritical airfoils
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Deep learning in fluid dynamics
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Flow field prediction of supercritical airfoils via variational autoencoder based deep learning framework
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A deep learning based prediction approach for the supercritical airfoil at transonic speeds
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Closed-loop plasma flow control of a turbulent cylinder wake flow using machine learning at Reynolds number of 28 000
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A Style-Based Generator Architecture for Generative Adversarial Networks
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Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
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Scalable Diffusion Models with Transformers
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A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications
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Convolutional Neural Networks for Steady Flow Approximation
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FiLM: Visual Reasoning with a General Conditioning Layer
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Deep Learning Methods for Reynolds-Averaged Navier–Stokes Simulations of Airfoil Flows
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Efficient Aerodynamic Shape Optimization with Deep-Learning-Based Geometric Filtering
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Fast Predictions of Aircraft Aerodynamics Using Deep-Learning Techniques
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A Universal Parametric Geometry Representation Method - "CST"
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Fast Predictions of Aircraft Aerodynamics using Deep Learning Techniques
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Exploiting Generative AI to Scale up Intelligent Tutoring Systems
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FiLM: Visual Reasoning with a General Conditioning Layer
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An Introduction to Image Synthesis with Generative Adversarial Nets
inferredcites →https://doi.org/10.48550/arxiv.1805.08318openalex-snapshot
Self-Attention Generative Adversarial Networks
inferredcites →https://doi.org/10.48550/arxiv.1809.11096openalex-snapshot
Large Scale GAN Training for High Fidelity Natural Image Synthesis
inferredcites →https://doi.org/10.48550/arxiv.2010.11929openalex-snapshot
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
inferredcites →https://doi.org/10.48550/arxiv.2102.07074openalex-snapshot
TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up
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Diffusion Models Beat GANs on Image Synthesis
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ViTGAN: Training GANs with Vision Transformers
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Machine Learning for Fluid Mechanics
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Generative AI Driven Aerodynamic Shape Optimization: A Neural Network-Based Framework for Enhancing Performance and Efficiency
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