Scenario adaptive disruption prediction study for next generation burning-plasma tokamaks. - Jinxiang Zhu; Cristina Rea; Robert S. Granetz; Earl S. Marmar; Kevin J. Montes; Ryan Sweeney; Roy A. Tinguely; Dalong Chen; Biao Shen; Bingjia Xiao; David Humphreys; Jayson Barr; et al. (CoRR, 2021)

Transferable Cross-Tokamak Disruption Prediction with Deep Hybrid Neural Network Feature Extractor. - Wei Zheng; Fengming Xue; Ming Zhang; Zhongyong Chen; Chengshuo Shen; Xinkun Ai; Nengchao Wang; Dalong Chen; Bihao Guo; Yonghua Ding; Zhipeng Chen; Zhoujun Yang; et al. (CoRR, 2022)

Disruption Precursor Onset Time Study Based on Semi-supervised Anomaly Detection. - Xinkun Ai; Wei Zheng; Ming Zhang; Dalong Chen; Chengshuo Shen; Bihao Guo; Bingjia Xiao; Yu Zhong; Nengchao Wang; Zhoujun Yang; Zhipeng Chen; Zhongyong Chen; et al. (CoRR, 2023)

Feature-based Transferable Disruption Prediction for future tokamaks using domain adaptation. - Chengshuo Shen; Wei Zheng; Bihao Guo; Dalong Chen; Xinkun Ai; Fengming Xue; Yu Zhong; Nengchao Wang; Biao Shen; Binjia Xiao; Yonghua Ding; Zhongyong Chen; et al. (CoRR, 2023)

FeatWalk: Enhancing Few-Shot Classification through Local View Leveraging. - Dalong Chen; Jianjia Zhang; Wei-Shi Zheng 001; Ruixuan Wang (AAAI, 2024)