Publication

Classification of tokamak plasma confinement states with convolutional recurrent neural networks

Related publications (30)

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We discuss how the combination of experimental observations and rapid modeling has enabled to improve understanding of the tokamak ramp-down phase in ASDEX Upgrade. A series of dedicated experiments has been performed, to disentangle the effect of individu ...

Iop Publishing Ltd2024

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Olivier Sauter, Stefano Coda, Alexander Karpushov, Yann Camenen, Benoît Labit, Antoine Pierre Emmanuel Alexis Merle, Olivier Claude Martin Février, Simon Van Mulders, Filippo Bagnato, Alessandro Pau, Matteo Vallar, Cassandre Ekta Contré, Stefano Marchioni, Oleg Krutkin, Reinart Andreas J. Coosemans

Under the auspices of EUROfusion, the ITER baseline (IBL) scenario has been jointly investigated on AUG and TCV in the past years and this paper reports on the developments on TCV. It is found that the performance of TCV IBL is mainly limited by (neoclassi ...

2024

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Carbon impurity transport is studied in the TCV tokamak using a charge exchange recombination diagnostic. TCVs flexible shaping capabilities were exploited to extend previous impurity transport studies to negative triangularity (delta < 0). A practical way ...

Iop Publishing Ltd2024

Topics in statistical physics of high-dimensional machine learning

Hugo Chao Cui

In the past few years, Machine Learning (ML) techniques have ushered in a paradigm shift, allowing the harnessing of ever more abundant sources of data to automate complex tasks. The technical workhorse behind these important breakthroughs arguably lies in ...

EPFL2024

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Axel Bisi, Alberto Silvio Chiappa, Alexander Mathis, Alessandro Marin Vargas

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EPFL Infoscience2024

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The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

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The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

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Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Romain Christophe Rémy Fleury, Janez Rus

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

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Partial discharge localization in power transformer tanks using machine learning methods

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Nature Publishing Group2024

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

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The field of biometrics, and especially face recognition, has seen a wide-spread adoption the last few years, from access control on personal devices such as phones and laptops, to automated border controls such as in airports. The stakes are increasingly ...

EPFL2024