| Time-Series Representation Learning via Temporal and Contextual Contrasting E Eldele, M Ragab, Z Chen, M Wu, CK Kwoh, X Li, C Guan International Joint Conferences on Artificial Intelligence (IJCAI'21), 2352 …, 2021 | 533 | 2021 |
| An attention-based deep learning approach for sleep stage classification with single-channel EEG E Eldele, Z Chen, C Liu, M Wu, CK Kwoh, X Li, C Guan IEEE Transactions on Neural Systems and Rehabilitation Engineering 29, 809-818, 2021 | 470 | 2021 |
| Self-supervised contrastive representation learning for semi-supervised time-series classification E Eldele, M Ragab, Z Chen, M Wu, CK Kwoh, X Li, C Guan IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023 | 101 | 2023 |
| Conditional contrastive domain generalization for fault diagnosis M Ragab, Z Chen, W Zhang, E Eldele, M Wu, CK Kwoh, X Li IEEE Transactions on Instrumentation and Measurement 71, 1-12, 2022 | 83 | 2022 |
| Adatime: A benchmarking suite for domain adaptation on time series data M Ragab, E Eldele, WL Tan, CS Foo, Z Chen, M Wu, CK Kwoh, X Li ACM Transactions on Knowledge Discovery from Data 17 (8), 1-18, 2023 | 75 | 2023 |
| Self-supervised autoregressive domain adaptation for time series data M Ragab, E Eldele, Z Chen, M Wu, CK Kwoh, X Li IEEE Transactions on Neural Networks and Learning Systems 35 (1), 1341-1351, 2022 | 60 | 2022 |
| ADAST: Attentive Cross-Domain EEG-Based Sleep Staging Framework With Iterative Self-Training E Eldele, M Ragab, Z Chen, M Wu, CK Kwoh, X Li, C Guan IEEE Transactions on Emerging Topics in Computational Intelligence, 2022 | 47 | 2022 |
| Contrastive domain adaptation for time-series via temporal mixup E Eldele, M Ragab, Z Chen, M Wu, CK Kwoh, X Li IEEE Transactions on Artificial Intelligence, 2023 | 33* | 2023 |
| ECGTransForm: Empowering adaptive ECG arrhythmia classification framework with bidirectional transformer H El-Ghaish, E Eldele Biomedical Signal Processing and Control 89, 105714, 2024 | 29 | 2024 |
| TSLANet: Rethinking transformers for time series representation learning E Eldele, M Ragab, Z Chen, M Wu, X Li International Conference on Machine Learning (ICML), 2024 | 28 | 2024 |
| Self-supervised Learning for Label-Efficient Sleep Stage Classification: A Comprehensive Evaluation E Eldele, M Ragab, Z Chen, M Wu, CK Kwoh, X Li IEEE Transactions on Neural Systems and Rehabilitation Engineering 31, 1333-1342, 2023 | 28 | 2023 |
| Label-efficient time series representation learning: A review E Eldele, M Ragab, Z Chen, M Wu, CK Kwoh, X Li IEEE Transactions on Artificial Intelligence, 2024 | 20 | 2024 |
| Source-free domain adaptation with temporal imputation for time series data M Ragab, E Eldele, M Wu, CS Foo, X Li, Z Chen Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 13 | 2023 |
| Evidentially calibrated source-free time-series domain adaptation with temporal imputation M Ragab, P Gong, E Eldele, W Zhang, M Wu, CS Foo, D Zhang, X Li, ... arXiv preprint arXiv:2406.02635, 2024 | 2 | 2024 |
| MSA-CNN: A Lightweight Multi-Scale CNN with Attention for Sleep Stage Classification S Goerttler, Y Wang, E Eldele, M Wu, F He arXiv preprint arXiv:2501.02949, 2025 | 1 | 2025 |
| Hierarchical Classification Auxiliary Network for Time Series Forecasting Y Sun, Z Xie, D Chen, E Eldele, Q Hu arXiv preprint arXiv:2405.18975, 2024 | 1 | 2024 |
| Towards robust and label-efficient time series representation learning EAIA Eldele Nanyang Technological University, 2023 | 1 | 2023 |
| Retrieving Filter Spectra in CNN for Explainable Sleep Stage Classification S Goerttler, Y Wang, E Eldele, F He, M Wu arXiv preprint arXiv:2502.06478, 2025 | | 2025 |
| Learning Pattern-Specific Experts for Time Series Forecasting Under Patch-level Distribution Shift Y Sun, Z Xie, E Eldele, D Chen, Q Hu, M Wu arXiv preprint arXiv:2410.09836, 2024 | | 2024 |
| Bi-hemisphere Interaction Convolutional Neural Network for Motor Imagery Classification X Lin, E Eldele, Z Chen, M Wu, HW Ng, C Guan 2024 46th Annual International Conference of the IEEE Engineering in …, 2024 | | 2024 |
Wu MinPrincipal Scientist, Institute for Infocomm ResearchEmail verificata su i2r.a-star.edu.sg