K. Montes

发表

PSFC/JA-21-6 Disruption Prevention via Interpretable Data-Driven Algorithms On DIII-D and EAST

C. Rea, J. Barr, R. Granetz, 2021 .

Nested cross-validation loop for performance optimization in imbalanced problems

Kevin Montes, Cristina Rea, Robert S. Granetz, 2018 .

A Machine Learning-based Real Time Disruption Predictor on DIII-D

N. W. Eidietis, Kevin Montes, Cristina Rea, 2018 .

Disruption prediction: from shallow to deep learning and interpretability techniques

Kevin Montes, Cristina Rea, Robert S. Granetz, 2018 .

Hybrid deep-learning architecture for general disruption prediction across multiple tokamaks

R. A. Tinguely, R. Sweeney, C. Rea, 2020, Nuclear Fusion.

A real-time machine learning-based disruption predictor in DIII-D

Kevin Montes, Cristina Rea, Robert S. Granetz, 2019, Nuclear Fusion.

Progress Toward Interpretable Machine Learning–Based Disruption Predictors Across Tokamaks

Cristina Rea, Robert Granetz, Kevin Montes, 2020 .

Scenario adaptive disruption prediction study for next generation burning-plasma tokamaks

R. Sweeney, O. Meneghini, R. A. Tinguely, 2021, Nuclear Fusion.

Real-time prediction of high-density EAST disruptions using random forest

R. Granetz, Y. Huang, J. Qian, 2021, Nuclear Fusion.

Machine learning for disruption warnings on Alcator C-Mod, DIII-D, and EAST

N. W. Eidietis, Orso Meneghini, Mark D. Boyer, 2019, Nuclear Fusion.

Disruption prediction investigations using Machine Learning tools on DIII-D and Alcator C-Mod

N. W. Eidietis, Kevin Montes, Cristina Rea, 2018, Plasma Physics and Controlled Fusion.

A semi-supervised machine learning detector for physics events in tokamak discharges

R. A. Tinguely, R. Granetz, R. Sweeney, 2020 .

An application of survival analysis to disruption prediction via Random Forests

R. A. Tinguely, K. J. Montes, C. Rea, 2019, Plasma Physics and Controlled Fusion.