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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 / 153 papers shown
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review
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Physics Informed Neural Network for Dynamic Stress Prediction
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137
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227
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Leveraging Stochastic Predictions of Bayesian Neural Networks for Fluid Simulations
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138
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26 Apr 2022
DL4SciVis: A State-of-the-Art Survey on Deep Learning for Scientific Visualization
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13 Apr 2022
Learning Similarity Metrics for Volumetric Simulations with Multiscale CNNs
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08 Feb 2022
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326
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Latent Space Simulation for Carbon Capture Design Optimization
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Factorized Fourier Neural Operators
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400
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Resistance-Time Co-Modulated PointNet for Temporal Super-Resolution Simulation of Blood Vessel Flows
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Fei Gao
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Timon Rabczuk
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Learn-Morph-Infer: a new way of solving the inverse problem for brain tumor modeling
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Kevin Scibilia
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Antonio Terpin
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Fernando Navarro
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Bjoern Menze
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Deep Generative Models in Engineering Design: A Review
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3DV
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341
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Exploratory Lagrangian-Based Particle Tracing Using Deep Learning
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Sudhanshu Sane
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172
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A Review of Physics-based Machine Learning in Civil Engineering
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180
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Learning Transport Processes with Machine Intelligence
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183
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Physics-informed Convolutional Neural Networks for Temperature Field Prediction of Heat Source Layout without Labeled Data
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Model reduction for the material point method via an implicit neural representation of the deformation map
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Performance and accuracy assessments of an incompressible fluid solver coupled with a deep Convolutional Neural Network
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115
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233
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Application of Video-to-Video Translation Networks to Computational Fluid Dynamics
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An Extensible Benchmark Suite for Learning to Simulate Physical Systems
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Joan Bruna
Daniele Panozzo
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T. Schneider
Denis Zorin
168
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Physics-Guided Deep Learning for Dynamical Systems: A Survey
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AI4CE
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490
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Physics perception in sloshing scenes with guaranteed thermodynamic consistency
B. Moya
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D. González
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Elías Cueto
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