Cross-LKTCN: Modern Convolution Utilizing Cross-Variable Dependency for Multivariate Time Series Forecasting Dependency for Multivariate Time Series Forecasting. - Donghao Luo 002; Xue Wang (CoRR, 2023)

ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis. - Donghao Luo 002; Xue Wang (ICLR, 2024)

DeformableTST: Transformer for Time Series Forecasting without Over-reliance on Patching. - Donghao Luo 002; Xue Wang (NeurIPS, 2024)

Few-shot unseen defect segmentation for polycrystalline silicon panels with an interpretable dual subspace attention variational learning framework. - Haiming Yao; Wei Luo; Wenyong Yu; Xiaotian Zhang; Zhenfeng Qiang; Donghao Luo 002; Hui Shi (Adv. Eng. Informatics, 2024)

Local-global normality learning and discrepancy normalizing flow for unsupervised image anomaly detection. - Haiming Yao; Wei Luo; Weihang Zhang; Xiaotian Zhang; Zhenfeng Qiang; Donghao Luo 002 (Eng. Appl. Artif. Intell., 2024)

Learning Global-Local Correspondence With Semantic Bottleneck for Logical Anomaly Detection. - Haiming Yao; Wenyong Yu; Wei Luo; Zhenfeng Qiang; Donghao Luo 002; Xiaotian Zhang (IEEE Trans. Circuits Syst. Video Technol., 2024)

Dual-Attention Transformer and Discriminative Flow for Industrial Visual Anomaly Detection. - Haiming Yao; Wei Luo; Wenyong Yu; Xiaotian Zhang; Zhenfeng Qiang; Donghao Luo 002; Hui Shi (IEEE Trans Autom. Sci. Eng., 2024)