Fully convolutional surrogate models trained on 64×64 patches predict 256×256 reactive-flow fields with competitive accuracy and lower GPU memory than full-domain or reduced-order models.
A patch-based convolutional neu- ral network for remote sensing image classification.Neural Networks, 95:19–28, 2017
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Surrogate models for Rock-Fluid Interaction: A Grid-Size-Invariant Approach
Fully convolutional surrogate models trained on 64×64 patches predict 256×256 reactive-flow fields with competitive accuracy and lower GPU memory than full-domain or reduced-order models.