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2020 – today
- 2024
[i1]Chun-Kai Huang, Yi-Hsien Hsieh, Ta-Jung Chien, Li-Cheng Chien, Shao-Hua Sun, Tung-Hung Su, Jia-Horng Kao, Che Lin:
Scalable Numerical Embeddings for Multivariate Time Series: Enhancing Healthcare Data Representation Learning. CoRR abs/2405.16557 (2024)- 2023
- [c4]Hsu-Hsiang Chang, Te-Cheng Hsu, Yi-Hsien Hsieh, Che Lin:
Meta-EHR: A meta-learning approach for electronic health records with a high imbalanced ratio and missing rate. EMBC 2023: 1-4 - [c3]Yi-Hsien Hsieh, Jung-Chi Hsu, Che Lin, Lian-Yu Lin:
X-RIM: Extreme Recurrent Independent Mechanisms for Noise-resistant and Interpretable Stroke Risk Prediction. EMBC 2023: 1-4 - [c2]Tzu-Chen Huang, Te-Cheng Hsu, Yi-Hsien Hsieh, Che Lin:
Utilizing Graph Neural Networks for Breast Cancer Prognosis Prediction with High-dimensional Genomic Data. EMBC 2023: 1-4 - [c1]Tanoj Langore, Te-Cheng Hsu, Yi-Hsien Hsieh, Che Lin:
LE-DTA: Local Extrema Convolution for Drug Target Affinity Prediction. ICASSP 2023: 1-5
2010 – 2019
- 2016
- [j1]Shao-Ku Kao, Yi-Hsien Hsieh, Hsiang-Chi Cheng:
An all-digital DLL with duty-cycle correction using reusable TDC. Int. J. Circuit Theory Appl. 44(5): 1055-1070 (2016)
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