Dan Lu Senior Staff Scientist Contact . . | LUD1@ORNL.GOV All Publications An Alternative Ensemble Streamflow Prediction Approach Using Improved Subseasonal Precipitation Forecasts from the North America Multi-Model Ensemble Phase II Recommendations for Comprehensive and Independent Evaluation of Machine Learning-Based Earth System Models A novel conditional generative model for efficient ensemble forecasts of state variables in large-scale geological carbon storage Machine learning opportunities for nucleosynthesis studies Distance preserving machine learning for uncertainty aware accelerator capacitance predictions ExoTST: Exogenous-Aware Temporal Sequence Transformer for Time Series Prediction A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability... Probabilistic neural networks for improved analyses with phenomenological R-matrix Comparison of machine learning and electrical resistivity arrays to inverse modeling for locating and characterizing subsurface targets Improving streamflow predictions across CONUS by integrating advanced machine learning models and diverse data FutureTST: When Transformers Meet Future Exogenous Drivers A Diffusion-Based Uncertainty Quantification Method to Advance E3SM Land Model Calibration 91°µÍø's Strategic Research and Development Insights for Digital Twins Advancing earth system model calibration: a diffusion-based method Improving Streamflow predictions with vision transformers... Improving the estimation of atmospheric water vapor pressure using interpretable long short-term memory networks 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 Accelerating Scientific Simulations with Bi-Fidelity Weighted Transfer Learning Multi-module-based CVAE to predict HVCM faults in the SNS accelerator Knowledge-Informed Uncertainty-Aware Machine Learning for Time Series Forecasting of Dynamical Engineered Systems Uncertainty quantification of the convolutional neural networks on permeability estimation from micro-CT scanned sandstone and carbonate rock images Uncertainty Quantification of Capacitor Switching Transient Location using Machine Learning Pagination Current page 1 Page 2 Page 3 … Next page ›â¶Äº Last page Last » Key Links Curriculum Vitae Organizations Computing and Computational Sciences Directorate Computational Sciences and Engineering Division Advanced Computing Methods for Physical Sciences Section Computational Earth Sciences Group
