Te-Cheng Hsu — accepted AI-conference papers

2023

LE-DTA: Local Extrema Convolution for Drug Target Affinity Prediction

Tanoj Langore, Te-Cheng Hsu, Yi-Hsien Hsieh, Che Lin

ICASSP 2023accepted

One of the essential parts of drug discovery and design is the prediction of drug-target affinity (DTA). Researchers have proposed computational approaches for predicting DTA to circumvent the more expensive in vivo and in vitro tests. More recent approaches employed deep network architectures to ob…

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2019

Enhanced Recurrent Neural Network for Combining Static and Dynamic Features for Credit Card Default Prediction

Te-Cheng Hsu, Shing-Tzuo Liou, Yun-Ping Wang, Yung-Shun Huang, Che Lin

ICASSP 2019accepted

Deep learning models have been shown to be capable of extracting high-level representations from the increasing amount of customer-level data generated via fast-growing financial activities. In financial data, dynamic features that evolve with time are commonly observed. However, such time dependenc…

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