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1806.02071
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Deep Fluids: A Generative Network for Parameterized Fluid Simulations
6 June 2018
Byungsoo Kim
Vinicius Azevedo
N. Thürey
Theodore Kim
Markus Gross
B. Solenthaler
GAN
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Papers citing
"Deep Fluids: A Generative Network for Parameterized Fluid Simulations"
50 / 151 papers shown
Title
A Flow-rate-conserving CNN-based Domain Decomposition Method for Blood Flow Simulations
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Precise Gradient Discontinuities in Neural Fields for Subspace Physics
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02 Apr 2025
Learning Distributions of Complex Fluid Simulations with Diffusion Graph Networks
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179
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Stabilizing Backpropagation Through Time to Learn Complex Physics
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144
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Multi-fidelity physics constrained neural networks for dynamical systems
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Rossella Arcucci
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215
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Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks
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Xihaier Luo
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173
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Fluid Simulation on Neural Flow Maps
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138
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Weak-Form Latent Space Dynamics Identification
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April Tran
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David M. Bortz
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Yong Chul Ju
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152
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196
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209
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284
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HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction
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172
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High Throughput Training of Deep Surrogates from Large Ensemble Runs
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129
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Deep Learning in Deterministic Computational Mechanics
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267
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Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation
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273
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A multiscale and multicriteria Generative Adversarial Network to synthesize 1-dimensional turbulent fields
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From Zero to Turbulence: Generative Modeling for 3D Flow Simulation
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414
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211
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International Conference on Learning Representations (ICLR), 2023
Erik Franz
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