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We propose MeshfreeFlowNet, a novel deep learning-based super-resolution framework to generate continuous (grid-free) spatio-temporal solutions from the low-resolution inputs.
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Adaptive fully implicit multi-scale finite-volume method for multi-phase flow and transport in heterogeneous porous media
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Image super-resolution as sparse representation of raw image patches
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A Unified Modeling Approach to Climate System Prediction
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Multiscale modeling of multiphase flow with complex interactions , volume 1
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Simulations of multiphase flows with multiple length scales using moving mesh interface tracking with adaptive meshing
Shaoping Quan · 2011
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Image and video upscaling from local self-examples
Gilad Freedman and Raanan Fattal · 2011
A Fully Progressive Approach to Single-Image Super-Resolution
Yifan Wang, Federico Perazzi, Brian McWilliams, Alexander Sorkine-Hornung, Olga Sorkine-Hornung, and Christopher Schroers · 2018
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Deep Photo Enhancer: Unpaired Learning for Image Enhancement from Photographs with GANs
Yu Sheng Chen, Yu Ching Wang, Man Hsin Kao, and Yung Yu Chuang · 2018
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A Variational U-Net for Conditional Appearance and Shape Generation Heidelberg Collaboratory for Image Processing
Patrick Esser and Ekaterina Sutter · 2018
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Multiscale modeling of compartmentalized reservoirs using a hybrid clustering-based non-local approach
Soheil Esmaeilzadeh, Amir Salehi, Gill Hetz, Feyisayo Olalotiti-lawal, Hamed Darabi, and David Castineira · 2019
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A General Spatio-Temporal Clustering-Based Non-Local Formulation for Multiscale Modeling of Compartmentalized Reservoirs
Soheil Esmaeilzadeh, Amir Salehi, Gill Hetz, Feyisayo Olalotiti-lawal, Hamed Darabi, and David Castineira · 2019
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Improving NASA’s Multiscale Modeling Framework for Tropical Cyclone Climate Study
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Perceptual Losses for Real-Time Style Transfer and Super-Resolution
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4d spatio-temporal convnets: Minkowski convolutional neural networks
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Two-Phase Multiscale Numerical Framework for Modeling Thin Films on Curved Solid Surfaces in Porous Media
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