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Siyan Liu

Contact

LIUS1@ORNL.GOV

Publications

December 2024

Integrated edge-to-exascale workflow for real-time steering in neutron scattering experiments

Journal: Structural Dynamics
November 2024

A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics

Conference Paper
November 2024

ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability...

Journal: The International Conference for High Performance Computing, Networking, Storage, and Analysis
December 2023

Advancing subseasonal reservoir inflow forecasts using an explainable machine learning method...

Journal: Journal of Hydrology: Regional Studies
December 2023

Explainable machine learning model for multi-step forecasting of reservoir inflow with uncertainty…

Journal: Environmental Modelling & Software

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Related News

News

Calculations on Frontier earns Gordon Bell Prize, ORNL major presence at SC24

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Fine-tuning forecasts: ORBIT brings long-range weather prediction within reach

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An Interpretable Machine Learning Model for Advancing Time Series Predictions

Research Highlight

A Prediction Interval Method for Machine Learning Model Uncertainty Quantification
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