Chengshuo Shen

According to our database, Chengshuo Shen authored at least 6 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2024

Enantiomerization of five-membered-heterocycle-embedded helicenes: A DFT study.

Xunshan Liu, Zhen Liang, Zhetong Jin, Xu Zhang, Chengshuo Shen

J. Comput. Chem., March, 2024

2023

Extraction of n = 0 pick-up by locked mode detectors based on neural networks in J-TEXT.

Chengshuo Shen, Jianchao Li, Yonghua Ding, Jiaolong Dong, Nengchao Wang, Dongliang Han, Feiyue Mao, Da Li, Zhipeng Chen, Zhoujun Yang, Zhongyong Chen, Yuan Pan, J.-TEXT team

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, Yuan Pan, J.-TEXT team

CoRR, 2023

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, Yonghua Ding, Yuan Pan, J.-TEXT team

CoRR, 2023

2022

IDP-PGFE: An Interpretable Disruption Predictor based on Physics-Guided Feature Extraction.

Chengshuo Shen, Wei Zheng, Yonghua Ding, Xinkun Ai, Fengming Xue, Yu Zhong, Nengchao Wang, Li Gao, Zhipeng Chen, Zhoujun Yang, Zhongyong Chen, Yuan Pan, J.-TEXT team

CoRR, 2022

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, Biao Shen, Bingjia Xiao, Yuan Pan

CoRR, 2022