Distance preserving machine learning for uncertainty aware accelerator capacitance predictions.
Mach. Learn. Sci. Technol., 2024
GenAI4UQ: A Software for Inverse Uncertainty Quantification Using Conditional Generative Models.
CoRR, 2024
Sequence Length Scaling in Vision Transformers for Scientific Images on Frontier.
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CoRR, 2024
ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability.
CoRR, 2024
Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation.
CoRR, 2024
A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics.
Proceedings of the SC24-W: Workshops of the International Conference for High Performance Computing, 2024
ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability.
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Proceedings of the International Conference for High Performance Computing, 2024
Explainable machine learning model for multi-step forecasting of reservoir inflow with uncertainty quantification.
Environ. Model. Softw., December, 2023
Multi-module based CVAE to predict HVCM faults in the SNS accelerator.
CoRR, 2023
Accelerating Scientific Simulations with Bi-Fidelity Weighted Transfer Learning.
Proceedings of the International Conference on Machine Learning and Applications, 2023
Time series anomaly detection in power electronics signals with recurrent and ConvLSTM autoencoders.
Digit. Signal Process., 2022
PI3NN: Out-of-distribution-aware Prediction Intervals from Three Neural Networks.
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
PI3NN: Prediction intervals from three independently trained neural networks.
CoRR, 2021
Enabling long-range exploration in minimization of multimodal functions.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021
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
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
A computer program for uncertainty analysis integrating regression and Bayesian methods.
Environ. Model. Softw., 2014