Yatao Bian

1.7k total citations
29 papers, 317 citations indexed

About

Yatao Bian is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Molecular Biology. According to data from OpenAlex, Yatao Bian has authored 29 papers receiving a total of 317 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 8 papers in Computational Theory and Mathematics and 7 papers in Molecular Biology. Recurrent topics in Yatao Bian's work include Advanced Graph Neural Networks (8 papers), Machine Learning in Materials Science (7 papers) and Computational Drug Discovery Methods (6 papers). Yatao Bian is often cited by papers focused on Advanced Graph Neural Networks (8 papers), Machine Learning in Materials Science (7 papers) and Computational Drug Discovery Methods (6 papers). Yatao Bian collaborates with scholars based in China, United States and Switzerland. Yatao Bian's co-authors include Junzhou Huang, Yu Rong, Tingyang Xu, Peilin Zhao, Erxue Min, Sophia Ananiadou, Weiyang Xie, Wenbing Huang, Hehuan Ma and Ran He and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Yatao Bian

27 papers receiving 307 citations

Peers

Yatao Bian
Comparison fields: 5 of 58
  • Artificial Intelligence 182
  • Computational Theory and Mathematics 80
  • Materials Chemistry 71
  • Computer Vision and Pattern Recognition 66
  • Molecular Biology 61
Replace Siqi Chen with:
Siqi Chen China
Daniel Zügner Germany
Konstantinos Pliakos Belgium
Yisong Yue United States
Hengtong Zhang United States
Zaixi Zhang China
Esra Akbaş United States
Jyothish Soman India
Robert Stanforth United Kingdom
Alberto García-Durán Switzerland
Siqi Chen China View profile →
Citations per field, relative to Yatao Bian
Yatao Bian · 1×
Citations per year, relative to Yatao Bian
Yatao Bian · 1×

Countries citing papers authored by Yatao Bian

Since Specialization
Citations

This map shows the geographic impact of Yatao Bian'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 Yatao Bian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yatao Bian more than expected).

Fields of papers citing papers by Yatao Bian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yatao Bian. 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 Yatao Bian. The network helps show where Yatao Bian may publish in the future.

Co-authorship network of co-authors of Yatao Bian

This figure shows the co-authorship network connecting the top 25 collaborators of Yatao Bian. A scholar is included among the top collaborators of Yatao Bian 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 Yatao Bian. Yatao Bian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 1
3 2
4 2
5 4
6 19
7 8
8 46
9 43
10
Not All Low-Pass Filters are Robust in Graph Convolutional Networks
14
11 38
12 21
13
Dual Message Passing Neural Network for Molecular Property Prediction.
5
14
GROVER: Self-supervised Message Passing Transformer on Large-scale Molecular Data.
6
15
Self-Supervised Graph Transformer on Large-Scale Molecular Data
12
16
Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference
1
17 3
18 2
19 2
20
Parallel Coordinate Descent Newton for Large-scale L1-Regularized Minimization.
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.

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