Weihua Li

According to our database, Weihua Li authored at least 16 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2024

RT-Transformer: retention time prediction for metabolite annotation to assist in metabolite identification.

Jun Xue, Bingyi Wang, Hongchao Ji, Weihua Li

Bioinform., March, 2024

2023

Learning spatiotemporal embedding with gated convolutional recurrent networks for translation initiation site prediction.

Weihua Li, Yanbu Guo, Bingyi Wang, Bei Yang

Pattern Recognit., April, 2023

Knowledge-aware representation learning for diagnosis prediction.

Weihua Li, Hang Li, Bei Yang, Lihua Zhou, Xianming Yang, Miao Zhang, Bingyi Wang

Expert Syst. J. Knowl. Eng., March, 2023

2022

Deep Effective <i>k</i>-mer representation learning for polyadenylation signal prediction via co-occurrence embedding.

Yanbu Guo, Hongxue Shen, Weihua Li, Chaoyang Li, Chen Jin

Knowl. Based Syst., 2022

Deep multi-scale Gaussian residual networks for contextual-aware translation initiation site recognition.

Yanbu Guo, Dongming Zhou, Weihua Li, Jinde Cao

Expert Syst. Appl., 2022

2021

Bidirectional LSTM-CRF Attention-based Model for Chinese Word Segmentation.

Chen Jin, Zhuangwei Shi, Weihua Li, Yanbu Guo

CoRR, 2021

Identifying polyadenylation signals with biological embedding via self-attentive gated convolutional highway networks.

Yanbu Guo, Dongming Zhou, Weihua Li, Jinde Cao, Rencan Nie, Lei Xiong, Xiaoli Ruan

Appl. Soft Comput., 2021

zk15120170770 at FakeDeS 2021: Fake news detection based on Pre-training Model.

Kun Zhao, Siyao Zhou, Weihua Li

Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2021) co-located with the Conference of the Spanish Society for Natural Language Processing (SEPLN 2021), 2021

2020

Attentive gated neural networks for identifying chromatin accessibility.

Yanbu Guo, Dongming Zhou, Weihua Li, Rencan Nie, Ruichao Hou, Chengli Zhou

Neural Comput. Appl., 2020

DeepANF: A deep attentive neural framework with distributed representation for chromatin accessibility prediction.

Yanbu Guo, Dongming Zhou, Rencan Nie, Xiaoli Ruan, Weihua Li

Neurocomputing, 2020

2019

基于贝叶斯网的短文本特征扩展方法 (Short Text Feature Extension Method Based on Bayesian Networks).

Huiqing Liu, Yanbu Guo, Hongling Li, Weihua Li

计算机科学, 2019

DeepACLSTM: deep asymmetric convolutional long short-term memory neural models for protein secondary structure prediction.

Yanbu Guo, Weihua Li, Bingyi Wang, Huiqing Liu, Dongming Zhou

BMC Bioinform., 2019

2018

Protein secondary structure prediction improved by recurrent neural networks integrated with two-dimensional convolutional neural networks.

Yanbu Guo, Bingyi Wang, Weihua Li, Bei Yang

J. Bioinform. Comput. Biol., 2018

2017

A novel method of text representation on hybrid neural networks.

Yanbu Guo, Chen Jin, Weihua Li, Chen Ji, Yuan Fang, Yunhao Duan

Proceedings of the 10th International Congress on Image and Signal Processing, 2017

2011

Constructing the Bayesian network structure from dependencies implied in multiple relational schemas.

Wei-Yi Liu, Kun Yue, Weihua Li

Expert Syst. Appl., 2011

2008

Recovering the Global Structure from Multiple Local Bayesian Networks.

Weihua Li, Weiyi Liu, Kun Yue

Int. J. Artif. Intell. Tools, 2008