Li, Xiang

Deep residual learning-based fault diagnosis method for rotating machinery

Zhang, W., Li, X., & Ding, Q. (2019) · ISA Transactions

Machine Fault Diagnosis TechniquesFault Detection and Control Systems

Cited by 416

Commonsense Knowledge Base Completion

Li, X., Taheri, A., Tu, L., & Gimpel, K. (2016) · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingAdvanced Graph Neural Networks

Cited by 166

Computational Screening of New Perovskite Materials Using Transfer Learning and Deep Learning

Li, X., Dan, Y., Dong, R., Cao, Z., Niu, C., Song, Y., Li, S., & Hu, J. (2019) · Applied Sciences

Machine Learning in Materials ScienceComputational Drug Discovery Methods

Cited by 74

TaGiTeD: Predictive Task Guided Tensor Decomposition for Representation Learning from Electronic Health Records

Yang, K., Li, X., Liu, H., Mei, J., Xie, G., Zhao, J., Xie, B., & Wang, F. (2017) · Proceedings of the AAAI Conference on Artificial Intelligence

Machine Learning in HealthcareTensor decomposition and applications

Cited by 30

A Physics-Guided Transformer for Robust State of Charge Estimation in Aging Lithium-Ion Batteries

Li, X., Wu, G., Chang, F., Xia, W., Sun, S., & Shen, Y. (2025) · Batteries

Battery Modeling and ManagementAdvancements in Battery Materials

Cited by 2