Disruption prediction using a full convolutional neural network on EAST

Predicting disruptive instabilities in controlled fusion plasmas through deep learning

(2019) Julian Kates-Harbeck et al.   NATURE

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

(2019) Kevin Joseph Montes et al.   NUCLEAR FUSION

Deep Learning for Plasma Tomography and Disruption Prediction From Bolometer Data

(2019) Diogo R. Ferreira et al.   IEEE TRANSACTIONS ON PLASMA SCIENCE

Adaptive predictors based on probabilistic SVM for real time disruption mitigation on JET

(2018) A. Murari et al.   NUCLEAR FUSION

Interpretation of machine-learning-based disruption models for plasma control

(2017) Matthew S Parsons   PLASMA PHYSICS AND CONTROLLED FUSION

Establishment and Assessment of Plasma Disruption and Warning Databases from EAST

(2016) Bo Wang et al.   PLASMA SCIENCE & TECHNOLOGY

Improvements in disruption prediction at ASDEX Upgrade

(2015) R. Aledda et al.   FUSION ENGINEERING AND DESIGN

The influence of an ITER-like wall on disruptions at JET

(2014) P. C. de Vries et al.   PHYSICS OF PLASMAS

The H-mode density limit in the full tungsten ASDEX Upgrade tokamak

(2014) M Bernert et al.   PLASMA PHYSICS AND CONTROLLED FUSION

Development of an efficient real-time disruption predictor from scratch on JET and implications for ITER

(2013) S. Dormido-Canto et al.   NUCLEAR FUSION

Survey of disruption causes at JET

(2011) P.C. de Vries et al.   NUCLEAR FUSION

Visual Navigation for Mobile Robots: A Survey

(2008) Francisco Bonin-Font et al.   JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS