Research graph
References from Physics-constrained deep learning for data assimilation of subsurface transport. Local targets link to admitted publications; unresolved targets remain external evidence.
Fundamentals, materials, and machine learning of polymer electrolyte membrane fuel cell technology
2020 · External reference
Unresolved reference
2007 · External reference
Comprehensive review of carbonated water injection for enhanced oil recovery
10.1016/j.fuel.2018.08.106 · 2019 · External reference
A comprehensive review on enhanced oil recovery by water alternating gas (Wag) injection
10.1016/j.fuel.2018.04.015 · 2018 · External reference
A review of the current progress of Co2 injection Eor and carbon storage in shale oil reservoirs
10.1016/j.fuel.2018.08.103 · 2019 · External reference
Unresolved reference
2010 · External reference
Model-data interaction in groundwater studies: review of methods, applications and future directions
10.1016/j.jhydrol.2018.09.053 · 2018 · External reference
Inverse modeling of subsurface flow and transport properties: a review with new developments
10.2136/vzj2007.0078 · 2008 · External reference
The Ncep/Ncar 40-year reanalysis project
10.1175/1520-0477(1996)077<0437:tnyrp>2.0.co;2 · 1996 · External reference
Uncertainty in hydrologic modeling: toward an integrated data assimilation framework
2007 · External reference
Unresolved reference
External reference
Unresolved reference
External reference
Machine learning for fluid mechanics
10.1146/annurev-fluid-010719-060214 · 2020 · External reference
Machine learning subsurface flow equations from data
10.1007/s10596-019-09847-2 · 2019 · External reference
Unresolved reference
2020 · External reference
Bayesian deep convolutional encoder–decoder networks for surrogate modeling and uncertainty quantification
10.1016/j.jcp.2018.04.018 · 2018 · External reference
Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data
10.1016/j.jcp.2019.05.024 · 2019 · External reference
Hidden fluid mechanics: learning velocity and pressure fields from flow visualizations
10.1126/science.aaw4741 · 2020 · External reference
Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
10.1016/j.jcp.2018.10.045 · 2019 · External reference
Physics-informed neural networks for multiphysics data assimilation with application to subsurface transport
10.1016/j.advwatres.2020.103610 · 2020 · External reference
Phiseg: capturing uncertainty in medical image segmentation
2019 · External reference
An uncertain future: forecasting from static images using variational autoencoders
2016 · External reference
Deep convolutional encoder-decoder networks for uncertainty quantification of dynamic multiphase flow in heterogeneous media
10.1029/2018wr023528 · 2019 · External reference
Segnet: a deep convolutional encoder-decoder architecture for image segmentation
10.1109/tpami.2016.2644615 · 2017 · External reference
Unresolved reference
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Unresolved reference
External reference
Tensorflow: a system for large-scale machine learning
2016 · External reference
Unresolved reference
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Unresolved reference
External reference
An approach to statistical spatial-temporal modeling of meteorological fields
10.1080/01621459.1994.10476754 · 1994 · External reference
Deconvolution and checkerboard artifacts
10.23915/distill.00003 · 2016 · External reference
Simple and scalable predictive uncertainty estimation using deep ensembles
2017 · External reference
Predicting effective diffusivity of porous media from images by deep learning
10.1038/s41598-019-56309-x · 2019 · External reference
