Ming Fan Contact fanm@ornl.gov All Publications Advancing spatiotemporal forecasts of CO 2 plume migration using deep learning networks with transfer learning and interpretation analysis Advancing subseasonal reservoir inflow forecasts using an explainable machine learning method... Explainable machine learning model for multi-step forecasting of reservoir inflow with uncertainty quantification A Comparative Study of Deep Learning Models for Fracture and Pore Space Segmentation in Synthetic Fractured Digital Rocks Uncertainty quantification of the convolutional neural networks on permeability estimation from micro-CT scanned sandstone and carbonate rock images Investigation of hydrometeorological influences on reservoir releases using explainable machine learning methods A deep learning-based direct forecasting of CO2 plume migration... A Spatiotemporal-Aware Weighting Scheme for Improving Climate Model Ensemble Predictions Identifying Hydrometeorological Factors Influencing Reservoir Releases Using Machine Learning Methods... Relative permeability as a stationary process: Energy fluctuations in immiscible displacement... Deep-learning-based workflow for boundary and small target segmentation in digital rock images using UNet++ and IK-EBM... Multimodel ensemble predictions of precipitation using bayesian neural networks... Multimodel Ensemble Predictions of Precipitation using Bayesian Neural Networks... Key Links Google Scholar ORCID GitHub Organizations Computing and Computational Sciences Directorate Computational Sciences and Engineering Division Advanced Computing Methods for Physical Sciences Section Computational Earth Sciences Group