Siyan Liu Contact lius1@ornl.gov All Publications 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... 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 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 Uncertainty quantification of machine learning models to improve streamflow prediction under changing climate and environmental conditions Investigation of hydrometeorological influences on reservoir releases using explainable machine learning methods A deep learning-based direct forecasting of CO2 plume migration... Improving net ecosystem CO2 flux prediction using memory-based interpretable machine learning Identifying Hydrometeorological Factors Influencing Reservoir Releases Using Machine Learning Methods 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 E... A prediction interval method for uncertainty quantification of regression models... Key Links ORCID
