Siyan Liu Contact LIUS1@ORNL.GOV All Publications Integrated edge-to-exascale workflow for real-time steering in neutron scattering experiments ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability... A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics Explainable machine learning model for multi-step forecasting of reservoir inflow with uncertainty quantification Advancing subseasonal reservoir inflow forecasts using an explainable machine learning method... Entropy-driven Optimal Sub-sampling of Fluid Dynamics for Developing Machine-learned Surrogates... 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 machine learning models to improve streamflow prediction under changing climate and environmental conditions Coupled Lattice Boltzmann Modeling Framework for Pore-Scale Fluid Flow and Reactive Transport... A scalable transformer model for real-time decision making in neutron scattering experiments Investigation of hydrometeorological influences on reservoir releases using explainable machine learning methods A deep learning-based direct forecasting of CO2 plume migration... Identifying Hydrometeorological Factors Influencing Reservoir Releases Using Machine Learning Methods... Improving net ecosystem CO2 flux prediction using memory-based interpretable machine learning An interpretable machine learning model for advancing terrestrial ecosystem predictions PI3NN: Out-of-distribution-aware Prediction Intervals from Three Neural Networks... An out-of-distribution-aware autoencoder model for reduced chemical kinetics A Review of Lattice-Boltzmann Models Coupled with Geochemical Modeling Applied for Simulation of Advanced Waterflooding and Enhanced Oil Recovery Processes A prediction interval method for uncertainty quantification of regression models... Key Links Google Scholar ORCID LinkedIn GitHub
Research Highlight A Prediction Interval Method for Machine Learning Model Uncertainty Quantification
