Dan Lu Senior Staff Scientist Contact lud1@ornl.gov All Publications Progress on Machine Learning for the SNS High Voltage Converter Modulators... An interpretable machine learning model for advancing terrestrial ecosystem predictions... Multimodel ensemble predictions of precipitation using bayesian neural networks... PI3NN: Out-of-distribution-aware Prediction Intervals from Three Neural Networks... Multimodel Ensemble Predictions of Precipitation using Bayesian Neural Networks... 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... Accurate and Timely Forecasts of Geologic Carbon Storage using Machine Learning Methods... An out-of-distribution-aware autoencoder model for reduced chemical kinetics... Enabling Long-range Exploration in Minimization of Multimodal Functions... A model-independent data assimilation (MIDA) module and its applications in ecology... Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators... Seasonal changes in GPP/SIF ratios and their climatic determinants across the Northern Hemisphere Boosting black-box adversarial attack via exploiting loss smoothness... A prediction interval method for uncertainty quantification of regression models... Streamflow Simulation in Data-Scarce Basins Using Bayesian and Physics-Informed Machine Learning Models Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators Multi‐hypothesis comparison of Farquhar and Collatz photosynthesis models reveals the unexpected influence of empirical ass... Efficient Distance-based Global Sensitivity Analysis for Terrestrial Ecosystem Modeling... Machine Learning Assisted Hybrid Models Can Improve Streamflow Simulation in Diverse Catchments across the Conterminous US... Learning-Based Inversion-Free Model-Data Integration to Advance Ecosystem Model Prediction... An Efficient Bayesian Method for Advancing the Application of Deep Learning in Earth Science Efficient surrogate modeling methods for large-scale Earth system models based on machine-learning techniques LIVVkit 2.1: automated and extensible ice sheet model validation... An adaptive Kriging surrogate method for efficient uncertainty quantification with an application to geological carbon seques... Pagination First page « First Previous page ‹‹ Page 1 Current page 2 Page 3 Next page ›› Last page Last » Key Links Curriculum Vitae Google Scholar ORCID GitHub Dan Lu's Website Organizations Computing and Computational Sciences Directorate Computational Sciences and Engineering Division Advanced Computing Methods for Physical Sciences Section Computational Earth Sciences Group