Dongxiao Zhang
Orcid: 0000-0001-6930-5994
According to our database1,
Dongxiao Zhang
authored at least 70 papers
between 1999 and 2024.
Collaborative distances:
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Bibliography
2024
Joint Motion Deblurring and Super-Resolution for Single Image Using Diffusion Model and GAN.
IEEE Signal Process. Lett., 2024
Int. J. Intell. Comput. Cybern., 2024
2023
IEEE Trans. Artif. Intell., December, 2023
CoRR, 2023
A knowledge-based data-driven (KBDD) framework for all-day identification of cloud types using satellite remote sensing.
CoRR, 2023
QIENet: Quantitative irradiance estimation network using recurrent neural network based on satellite remote sensing data.
CoRR, 2023
Revolutionizing Terrain-Precipitation Understanding through AI-driven Knowledge Discovery.
CoRR, 2023
CoRR, 2023
Discrete Point-Wise Attack is Not Enough: Generalized Manifold Adversarial Attack for Face Recognition.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
A comparative study of different granular structures induced from the information systems.
Soft Comput., 2022
Surrogate and inverse modeling for two-phase flow in porous media via theory-guided convolutional neural network.
J. Comput. Phys., 2022
Retention Time Prediction for Chromatographic Enantioseparation by Quantile Geometry-enhanced Graph Neural Network.
CoRR, 2022
TgDLF2.0: Theory-guided deep-learning for electrical load forecasting via Transformer and transfer learning.
CoRR, 2022
DISCOVER: Deep identification of symbolic open-form PDEs via enhanced reinforcement-learning.
CoRR, 2022
Discovery of partial differential equations from highly noisy and sparse data with physics-informed information criterion.
CoRR, 2022
Interpretable machine learning optimization (InterOpt) for operational parameters: a case study of highly-efficient shale gas development.
CoRR, 2022
Uncertainty quantification of two-phase flow in porous media via coupled-TgNN surrogate model.
CoRR, 2022
Inferring electrochemical performance and parameters of Li-ion batteries based on deep operator networks.
CoRR, 2022
Identification of Physical Processes and Unknown Parameters of 3D Groundwater Contaminant Problems via Theory-guided U-net.
CoRR, 2022
CoRR, 2022
CoRR, 2022
High-throughput discovery of chemical structure-polarity relationships combining automation and machine learning techniques.
CoRR, 2022
Deep-learning-based upscaling method for geologic models via theory-guided convolutional neural network.
CoRR, 2022
2021
Deep-learning based discovery of partial differential equations in integral form from sparse and noisy data.
J. Comput. Phys., 2021
Weak form theory-guided neural network (TgNN-wf) for deep learning of subsurface single- and two-phase flow.
J. Comput. Phys., 2021
Theory-guided hard constraint projection (HCP): A knowledge-based data-driven scientific machine learning method.
J. Comput. Phys., 2021
Editorial: Data Science Applications to Inverse and Optimization Problems in Earth Science.
Frontiers Appl. Math. Stat., 2021
Uncertainty quantification and inverse modeling for subsurface flow in 3D heterogeneous formations using a theory-guided convolutional encoder-decoder network.
CoRR, 2021
An Adaptive Deep Learning Framework for Day-ahead Forecasting of Photovoltaic Power Generation.
CoRR, 2021
Constructing Sub-scale Surrogate Model for Proppant Settling in Inclined Fractures from Simulation Data with Multi-fidelity Neural Network.
CoRR, 2021
RockGPT: Reconstructing three-dimensional digital rocks from single two-dimensional slice from the perspective of video generation.
CoRR, 2021
Any equation is a forest: Symbolic genetic algorithm for discovering open-form partial differential equations (SGA-PDE).
CoRR, 2021
Deep-Learning Discovers Macroscopic Governing Equations for Viscous Gravity Currents from Microscopic Simulation Data.
CoRR, 2021
2020
IEEE Trans. Geosci. Remote. Sens., 2020
DLGA-PDE: Discovery of PDEs with incomplete candidate library via combination of deep learning and genetic algorithm.
J. Comput. Phys., 2020
Comprehensive study and comparison of equilibrium and kinetic models in simulation of hydrate reaction in porous media.
J. Comput. Phys., 2020
Digital rock reconstruction with user-defined properties using conditional generative adversarial networks.
CoRR, 2020
Theory-guided hard constraint projection (HCP): a knowledge-based data-driven scientific machine learning method.
CoRR, 2020
CoRR, 2020
CoRR, 2020
Deep Learning of Dynamic Subsurface Flow via Theory-guided Generative Adversarial Network.
CoRR, 2020
Deep-learning of Parametric Partial Differential Equations from Sparse and Noisy Data.
CoRR, 2020
Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Network.
CoRR, 2020
2019
0-1 linear integer programming method for granule knowledge reduction and attribute reduction in concept lattices.
Soft Comput., 2019
Ground Deformation Revealed by Sentinel-1 MSBAS-InSAR Time-Series over Karamay Oilfield, China.
Remote. Sens., 2019
Co- and post-seismic Deformation Mechanisms of the M<sub>W</sub> 7.3 Iran Earthquake (2017) Revealed by Sentinel-1 InSAR Observations.
Remote. Sens., 2019
Neural Networks, 2019
Identification of physical processes via combined data-driven and data-assimilation methods.
J. Comput. Phys., 2019
DL-PDE: Deep-learning based data-driven discovery of partial differential equations from discrete and noisy data.
CoRR, 2019
2017
A two-stage adaptive stochastic collocation method on nested sparse grids for multiphase flow in randomly heterogeneous porous media.
J. Comput. Phys., 2017
2015
IEEE Signal Process. Lett., 2015
2014
J. Comput. Phys., 2014
Accelerating the iterative linear solver for reservoir simulation on multicore architectures.
Proceedings of the 20th IEEE International Conference on Parallel and Distributed Systems, 2014
2010
History matching of facies distribution with the EnKF and level set parameterization.
J. Comput. Phys., 2010
2008
Proceedings of the Quantitative Information Fusion for Hydrological Sciences, 2008
2007
Stochastic Simulations for Flow in Nonstationary Randomly Heterogeneous Porous Media Using a KL-Based Moment-Equation Approach.
Multiscale Model. Simul., 2007
2004
A Comparative Study on Uncertainty Quantification for Flow in Randomly Heterogeneous Media Using Monte Carlo Simulations and Conventional and KL-Based Moment-Equation Approaches.
SIAM J. Sci. Comput., 2004
1999
J. Comput. Sci. Technol., 1999