Dan Lu Senior Staff Scientist Contact LUD1@ORNL.GOV All Publications Uncertainty Quantification of Capacitor Switching Transient Location using Machine Learning Editorial: Data-driven machine learning for advancing hydrological and hydraulic predictability Stream Temperature Prediction in a Shifting Environment: Explaining the Influence of Deep Learning Architecture... Uncertainty quantification of machine learning models to improve streamflow prediction under changing climate and environmental conditions Machine-learning-assisted automation of single-crystal neutron diffraction Improving E3SM Land Model Photosynthesis Parameterization via Satellite SIF, Machine Learning, and Surrogate Modeling Investigation of hydrometeorological influences on reservoir releases using explainable machine learning methods Evaluation of distributed process-based hydrologic model performance using only a priori information to define model inputs Influence of fatigue precracking and specimen size on Master Curve fracture toughness measurements of EUROFER97 and F82H steels A deep learning-based direct forecasting of CO2 plume migration... A Spatiotemporal-Aware Weighting Scheme for Improving Climate Model Ensemble Predictions Machine Learning Assisted Reservoir Operation Model for Long-Term Water Management Simulation Improving net ecosystem CO2 flux prediction using memory-based interpretable machine learning Exploiting the Local Parabolic Landscapes of Adversarial Losses to Accelerate Black-Box Adversarial Attack Identifying Hydrometeorological Factors Influencing Reservoir Releases Using Machine Learning Methods... Time series anomaly detection in power electronics signals with recurrent and ConvLSTM autoencoders... Progress on Machine Learning for the SNS High Voltage Converter Modulators... PI3NN: Out-of-distribution-aware Prediction Intervals from Three Neural Networks... Multimodel Ensemble Predictions of Precipitation using Bayesian Neural Networks An interpretable machine learning model for advancing terrestrial ecosystem predictions Multimodel ensemble predictions of precipitation using bayesian neural networks Accurate and Timely Forecasts of Geologic Carbon Storage using Machine Learning Methods Accurate and Rapid Forecasts for Geologic Carbon Storage via Learning-Based Inversion-Free Prediction... Machine learning-enabled model-data integration for predicting subsurface water storage An out-of-distribution-aware autoencoder model for reduced chemical kinetics Pagination First page « First Previous page ‹â¶Ä¹ Page 1 Current 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
