Predicting lncRNA-protein interactions based on graph autoencoders and collaborative training. - Chen Jin; Zhuangwei Shi; Han Zhang 017; Yanbin Yin (BIBM, 2021)

A representation learning model based on variational inference and graph autoencoder for predicting lncRNA-disease associations. - Zhuangwei Shi; Han Zhang 017; Chen Jin; Xiongwen Quan; Yanbin Yin (BMC Bioinform., 2021)

Incorporating Transformer and LSTM to Kalman Filter with EM algorithm for state estimation. - Zhuangwei Shi (CoRR, 2021)

Bidirectional LSTM-CRF Attention-based Model for Chinese Word Segmentation. - Chen Jin; Zhuangwei Shi; Weihua Li 006; Yanbu Guo (CoRR, 2021)

ATTCry: Attention-based neural network model for protein crystallization prediction. - Chen Jin; Jianzhao Gao; Zhuangwei Shi; Han Zhang 017 (Neurocomputing, 2021)

Differential equation and probability inspired graph neural networks for latent variable learning. - Zhuangwei Shi (CoRR, 2022)

Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction. - Zhuangwei Shi; Yang Hu; Guangliang Mo; Jian Wu (CoRR, 2022)

Graph neural networks and attention-based CNN-LSTM for protein classification. - Zhuangwei Shi (CoRR, 2022)

MambaStock: Selective state space model for stock prediction. - Zhuangwei Shi (CoRR, 2024)

MambaLithium: Selective state space model for remaining-useful-life, state-of-health, and state-of-charge estimation of lithium-ion batteries. - Zhuangwei Shi (CoRR, 2024)