Jinshuai Bai

According to our database, Jinshuai Bai authored at least 9 papers between 2022 and 2024.

Collaborative distances:

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

2024

Reliable deep learning framework for the ground penetrating radar data to locate the horizontal variation in levee soil compaction.

Laith Alzubaidi, Hussein Khalefa Chlaib, Mohammed A. Fadhel, Yubo Chen, Jinshuai Bai, Ahmed Shihab Albahri, Yuantong Gu

Eng. Appl. Artif. Intell., 2024

HomoGenius: a Foundation Model of Homogenization for Rapid Prediction of Effective Mechanical Properties using Neural Operators.

Yizheng Wang, Xiang Li, Ziming Yan, Yuqing Du, Jinshuai Bai, Bokai Liu, Timon Rabczuk, Yinghua Liu

CoRR, 2024

2023

A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications.

Laith Alzubaidi, Jinshuai Bai, Aiman Al-Sabaawi, José Santamaría, Ahmed Shihab Albahri, Bashar Sami Nayyef Al-dabbagh, Mohammed A. Fadhel, Mohamed Manoufali, Jinglan Zhang, Ali H. Al-Timemy, Ye Duan, Amjed Abdullah, Laith Farhan, Yi Lu, Ashish Gupta, Felix Albu, Amin M. Abbosh, Yuantong Gu

J. Big Data, December, 2023

A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion.

Ahmed Shihab Albahri, Ali Mohammed, Mohammed A. Fadhel, Alhamzah Alnoor, Noor S. Baqer, Laith Alzubaidi, Osamah Shihab Albahri, Abdullah Hussein Alamoodi, Jinshuai Bai, Asma Salhi, José Santamaría, Chun Ouyang, Ashish Gupta, Yuantong Gu, Muhammet Deveci

Inf. Fusion, August, 2023

Towards Risk-Free Trustworthy Artificial Intelligence: Significance and Requirements.

Laith Alzubaidi, Aiman Al-Sabaawi, Jinshuai Bai, Ammar Dukhan, Ahmed H. Alkenani, Ahmed Al-Asadi, Haider A. Alwzwazy, Mohamed Manoufali, Mohammed A. Fadhel, Ahmed Shihab Albahri, Catarina Moreira, Chun Ouyang, Jinglan Zhang, José Santamaría, Asma Salhi, Freek Hollman, Ashish Gupta, Ye Duan, Timon Rabczuk, Amin M. Abbosh, Yuantong Gu

Int. J. Intell. Syst., 2023

Physics-informed radial basis network (PIRBN): A local approximating neural network for solving nonlinear PDEs.

Jinshuai Bai, Gui-Rong Liu, Ashish Gupta, Laith Alzubaidi, Xi-Qiao Feng, Yuantong Gu

CoRR, 2023

Physics-informed neural network for friction-involved nonsmooth dynamics problems.

Zilin Li, Jinshuai Bai, Huajing Ouyang, Saulo Martelli, Ming Tang, Hongtao Wei, Pan Liu, Wei-Ron Han, Yuantong Gu

CoRR, 2023

2022

Physics-guided deep learning for data scarcity.

Jinshuai Bai, Laith Alzubaidi, Qingxia Wang, Ellen Kuhl, Mohammed Bennamoun, Yuantong Gu

CoRR, 2022

An introduction to programming Physics-Informed Neural Network-based computational solid mechanics.

Jinshuai Bai, Hyogu Jeong, C. P. Batuwatta-Gamage, Shusheng Xiao, Qingxia Wang, C. M. Rathnayaka, Laith Alzubaidi, Gui-Rong Liu, Yuantong Gu

CoRR, 2022