Li, Xiaoli
Agency for Science, Technology and Research · Institute for Infocomm Research
7 papers on CoChatORCID 0000-0002-0762-6562
Most cited papers
- Verified
Time-Series Representation Learning via Temporal and Contextual Contrasting
Eldele, E., Ragab, M., Chen, Z., Wu, M., Kwoh, C. K., Li, X., & Guan, C. (2021) · Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
Time Series Analysis and ForecastingDomain Adaptation and Few-Shot Learning
Cited by 696
- Verified
Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data
Koutsoukas, A., Monaghan, K. J., Li, X., & Huan, J. (2017) · Journal of Cheminformatics
Computational Drug Discovery MethodsMachine Learning in Materials Science
Cited by 315
- Verified
Self-Supervised Contrastive Representation Learning for Semi-Supervised Time-Series Classification
Eldele, E., Ragab, M., Chen, Z., Wu, M., Kwoh, C.-K., Li, X., & Guan, C. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence
Time Series Analysis and ForecastingDomain Adaptation and Few-Shot Learning
Cited by 224
- Verified
Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Data
Wang, Y., Xu, Y., Yang, J., Wu, M., Li, X., Xie, L., & Chen, Z. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence
Time Series Analysis and ForecastingAdvanced Graph Neural Networks
Cited by 134
- Verified
A Hybrid Ensemble Deep Learning Approach for Early Prediction of Battery Remaining Useful Life
Xu, Q., Wu, M., Khoo, E., Chen, Z., & Li, X. (2023) · IEEE/CAA Journal of Automatica Sinica
Battery Modeling and ManagementAdvancements in Battery Materials
Cited by 119
- Verified
Adversarial Multiple-Target Domain Adaptation for Fault Classification
Ragab, M., Chen, Z., Wu, M., Li, H., Kwoh, C.-K., Yan, R., & Li, X. (2021) · IEEE Transactions on Instrumentation and Measurement
Machine Fault Diagnosis TechniquesDomain Adaptation and Few-Shot Learning
Cited by 90
- Verified
From Algorithm to Hardware: A Survey on Efficient and Safe Deployment of Deep Neural Networks
Geng, X., Wang, Z., Chen, C., Xu, Q., Xu, K., Jin, C., Gupta, M., Yang, X., Chen, Z., Sabry Aly, M. M., et al. (2025) · IEEE Transactions on Neural Networks and Learning Systems
Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques
Cited by 26
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