Scalable NPairLoss-Based Deep-ECG for ECG Verification. - Yu-Shan Tai; Yi-Ta Chen; An-Yeu Andy Wu (AIAI, 2021)

Compression-Aware Projection with Greedy Dimension Reduction for Convolutional Neural Network Activations. - Yu-Shan Tai; Chieh-Fang Teng; Cheng-Yang Chang; An-Yeu Andy Wu (ICASSP, 2022)

Learnable Mixed-precision and Dimension Reduction Co-design for Low-storage Activation. - Yu-Shan Tai; Cheng-Yang Chang; Chieh-Fang Teng; An-Yeu Andy Wu (SiPS, 2022)

TSPTQ-ViT: Two-Scaled Post-Training Quantization for Vision Transformer. - Yu-Shan Tai; Ming-Guang Lin; An-Yeu Andy Wu (ICASSP, 2023)

Joint Optimization of Dimension Reduction and Mixed-Precision Quantization for Activation Compression of Neural Networks. - Yu-Shan Tai; Cheng-Yang Chang; Chieh-Fang Teng; Yi-Ta Chen; An-Yeu Wu (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

Similarity-Aware Fast Low-Rank Decomposition Framework for Vision Transformers. - Yuan-June Luo; Yu-Shan Tai; Ming-Guang Lin; An-Yeu Andy Wu (ISCAS, 2024)

FQ4DM: Full Quantization for Diffusion Model. - Chieh-En Wang; Yu-Shan Tai; An-Yeu Wu (MLSP, 2024)

MPTQ-ViT: Mixed-PrecisionPost-TrainingQuantizationforVisionTransformer. - Yu-Shan Tai; An-Yeu Wu (CoRR, 2024)

AMP-ViT: Optimizing Vision Transformer Efficiency with Adaptive Mixed-Precision Post-Training Quantization. - Yu-Shan Tai; An-Yeu Andy Wu (WACV, 2025)

Quick Bypass Mechanism of Zero-Shot Diffusion-Based Image Restoration. - Yu-Shan Tai; An-Yeu Wu (CoRR, 2025)