Xianggen Liu

1.1k total citations · 2 hit papers
20 papers, 542 citations indexed

About

Xianggen Liu is a scholar working on Artificial Intelligence, Molecular Biology and Computational Theory and Mathematics. According to data from OpenAlex, Xianggen Liu has authored 20 papers receiving a total of 542 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 6 papers in Molecular Biology and 6 papers in Computational Theory and Mathematics. Recurrent topics in Xianggen Liu's work include Computational Drug Discovery Methods (5 papers), Protein Structure and Dynamics (4 papers) and Machine Learning in Materials Science (4 papers). Xianggen Liu is often cited by papers focused on Computational Drug Discovery Methods (5 papers), Protein Structure and Dynamics (4 papers) and Machine Learning in Materials Science (4 papers). Xianggen Liu collaborates with scholars based in China, United States and Canada. Xianggen Liu's co-authors include Sen Song, Xin Hu, Xinke Shen, Dan Zhang, Pengyong Li, Yunan Luo, Jian Peng, Yuankai Wu, Jianshuai Feng and Yuxuan Liang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and Information Sciences.

In The Last Decade

Xianggen Liu

20 papers receiving 532 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Contrastive Learning of Subject-Invariant EEG Representations for Cross-Subject Emotion Recognition

2022 165 citations Xinke Shen, Xianggen Liu et al. IEEE Transactions on Affective Computing profile →
MSGNet: Learning Multi-Scale Inter-series Correlations for Multivariate Time Series Forecasting

2024 62 citations Yuxuan Liang, Xianggen Liu et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →

Peers

Countries citing papers authored by Xianggen Liu

Since Specialization

Citations

This map shows the geographic impact of Xianggen Liu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xianggen Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xianggen Liu more than expected).

Fields of papers citing papers by Xianggen Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xianggen Liu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xianggen Liu. The network helps show where Xianggen Liu may publish in the future.

Co-authorship network of co-authors of Xianggen Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Xianggen Liu. A scholar is included among the top collaborators of Xianggen Liu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xianggen Liu. Xianggen Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	Anesthetic drug discovery with computer-aided drug design and machine learning 2024 ·SHILAP Revista de lepidopterología ·Xianggen Liu, (unknown), (unknown), Bowen Ke, Jiancheng Lv	11
2	TimeSQL: Improving multivariate time series forecasting with multi-scale patching and smooth quadratic loss 2024 ·Information Sciences ·(unknown), Haoxin Wang, Bixiong Li, (unknown), Yuankai Wu, Xianggen Liu	12
3	GPT-NAS: Neural Architecture Search Meets Generative Pre-Trained Transformer Model 2024 ·Big Data Mining and Analytics ·Caiyang Yu, Xianggen Liu, Yifan Wang, Yun Liu, (unknown), (unknown), Chenwei Tang, (unknown)	1
4	Deep simulated annealing for the discovery of novel dental anesthetics with local anesthesia and anti-inflammatory properties 2024 ·Acta Pharmaceutica Sinica B ·(unknown), Haofan Wang, Xianggen Liu, (unknown), (unknown), Wencheng Liu, Zhuang Miao, (unknown), Xianghua Yu, (unknown), (unknown), Ting Kang, (unknown), Yi Zhao, (unknown), (unknown), Ling Ye, Jin Liu, Xin‐hua Liang, Bowen Ke	4
5	TargetSA: adaptive simulated annealing for target-specific drug design 2024 ·Bioinformatics ·(unknown), (unknown), Wenhao Zheng, (unknown), Xianggen Liu	1
6	MSGNet: Learning Multi-Scale Inter-series Correlations for Multivariate Time Series Forecasting breakdown → 2024 ·Proceedings of the AAAI Conference on Artificial Intelligence ·(unknown), Yuxuan Liang, Xianggen Liu, Jianshuai Feng, Yuankai Wu	62
7	Vector-Quantized Prompt Learning for Paraphrase Generation 2023 ·(unknown), Yixin Liu, Peidong Liu, Xianggen Liu	1
8	Powerformer: A temporal-based transformer model for wind power forecasting 2023 ·Energy Reports ·(unknown), Haoxin Wang, Bixiong Li, (unknown), (unknown), Xianggen Liu	46
9	Contrastive Learning of Subject-Invariant EEG Representations for Cross-Subject Emotion Recognition breakdown → 2022 ·IEEE Transactions on Affective Computing ·Xinke Shen, Xianggen Liu, Xin Hu, Dan Zhang, Sen Song	165
10	Abstract Rule Learning for Paraphrase Generation 2022 ·Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence ·Xianggen Liu, Wenqiang Lei, Jiancheng Lv, (unknown)	2
11	Deep geometric representations for modeling effects of mutations on protein-protein binding affinity 2021 ·PLoS Computational Biology ·Xianggen Liu, Yunan Luo, Pengyong Li, Sen Song, Jian Peng	81
12	Simulated annealing for optimization of graphs and sequences 2021 ·Neurocomputing ·Xianggen Liu, Pengyong Li, Fandong Meng, Hao Zhou, (unknown), Jie Zhou, Lili Mou, Sen Song	22
13	Pairwise Half-graph Discrimination: A Simple Graph-level Self-supervised Strategy for Pre-training Graph Neural Networks 2021 ·Pengyong Li, Jun Wang, (unknown), Yixuan Qiao, Xianggen Liu, Fei Ma, Peng Gao, Sen Song, Guotong Xie	4
14	TrimNet: learning molecular representation from triplet messages for biomedicine 2020 ·Briefings in Bioinformatics ·Pengyong Li, Yuquan Li, Chang‐Yu Hsieh, Shengyu Zhang, Xianggen Liu, Huanxiang Liu, Sen Song, Xiaojun Yao	70
15	Riboexp: an interpretable reinforcement learning framework for ribosome density modeling 2020 ·Briefings in Bioinformatics ·Hailin Hu, Xianggen Liu, An Xiao, Yangyang Li, Chengdong Zhang, Tao Jiang, Dan Zhao, Sen Song, Jianyang Zeng	3
16	A Chance-Constrained Generative Framework for Sequence Optimization 2020 ·Xianggen Liu, Jian Peng, Qiang Liu, Sen Song	4
17	Finding decision jumps in text classification 2019 ·Neurocomputing ·Xianggen Liu, Lili Mou, (unknown), Zhengdong Lu, Sen Song	18
18	AddressNet: Shift-Based Primitives for Efficient Convolutional Neural Networks 2019 ·Yihui He, Xianggen Liu, (unknown), Yuchun Ma	18
19	Jumper: Learning When to Make Classification Decision in Reading 2018 ·Xianggen Liu, Lili Mou, (unknown), Zhengdong Lu, Sen Song	14
20	Searching safe landing site with parameters optimization based on genetic algorithm 2014 ·Xianggen Liu, (unknown), Sheng Chang, (unknown)	3

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact