Dan Lu
Orcid: 0000-0001-5162-9843Affiliations:
- Oak Ridge National Laboratory, Department of Computer Science and Mathmatics, TN, USA
- Florida State University, Tallahassee, FL, USA (PhD 2012)
According to our database1,
Dan Lu
authored at least 19 papers
between 2014 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Bibliography
2024
A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics.
CoRR, 2024
CoRR, 2024
Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation.
CoRR, 2024
2023
Explainable machine learning model for multi-step forecasting of reservoir inflow with uncertainty quantification.
Environ. Model. Softw., December, 2023
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies.
CoRR, 2023
2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Improving net ecosystem CO2 flux prediction using memory-based interpretable machine learning.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2022
Identifying Hydrometeorological Factors Influencing Reservoir Releases Using Machine Learning Methods.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2022
Exploiting the Local Parabolic Landscapes of Adversarial Losses to Accelerate Black-Box Adversarial Attack.
Proceedings of the Computer Vision - ECCV 2022, 2022
2021
CoRR, 2021
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021
2020
A Scalable Evolution Strategy with Directional Gaussian Smoothing for Blackbox Optimization.
CoRR, 2020
Efficient Distance-based Global Sensitivity Analysis for Terrestrial Ecosystem Modeling.
Proceedings of the 20th International Conference on Data Mining Workshops, 2020
2019
An adaptive Kriging surrogate method for efficient uncertainty quantification with an application to geological carbon sequestration modeling.
Comput. Geosci., 2019
Efficient surrogate modeling methods for large-scale Earth system models based on machine learning techniques.
CoRR, 2019
Learning-Based Inversion-Free Model-Data Integration to Advance Ecosystem Model Prediction.
Proceedings of the 2019 International Conference on Data Mining Workshops, 2019
An Efficient Bayesian Method for Advancing the Application of Deep Learning in Earth Science.
Proceedings of the 2019 International Conference on Data Mining Workshops, 2019
2014
A computer program for uncertainty analysis integrating regression and Bayesian methods.
Environ. Model. Softw., 2014