1. Corrigendum: Hybrid deep learning architecture for general disruption prediction across tokamaks (2021 Nucl. Fusion61 026007). (15th March 2021) Authors: Zhu, J. X.; Rea, C.; Montes, K.; Granetz, R. S.; Sweeney, R.; Tinguely, R. A. Journal: Nuclear fusion Issue: Volume 61:Number 4(2021) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
2. Magnetic energy dissipation during the current quench of disruption in EAST. (October 2020) Authors: Tang, T.; Zeng, L.; Chen, D. L.; Granetz, R. S.; Mao, S. T.; Duan, Y. M.; Zhang, L.; Zhuang, H. D.; Zhu, X.; Liu, H. Q.; Shen, B.; Jie, Y. X.; Gao, X. Journal: Journal of plasma physics Issue: Volume 86:Number 5(2020) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
3. Progress Toward Interpretable Machine Learning–Based Disruption Predictors Across Tokamaks. (16th November 2020) Authors: Rea, C.; Montes, K. J.; Pau, A.; Granetz, R. S.; Sauter, O. Journal: Fusion science and technology Issue: Volume 76:Number 8(2020) Page Start: 912 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗