Xue-Xin Wei

2.2k total citations
29 papers, 918 citations indexed

About

Xue-Xin Wei is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Artificial Intelligence. According to data from OpenAlex, Xue-Xin Wei has authored 29 papers receiving a total of 918 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Cognitive Neuroscience, 8 papers in Cellular and Molecular Neuroscience and 5 papers in Artificial Intelligence. Recurrent topics in Xue-Xin Wei's work include Neural dynamics and brain function (15 papers), Visual perception and processing mechanisms (9 papers) and Memory and Neural Mechanisms (6 papers). Xue-Xin Wei is often cited by papers focused on Neural dynamics and brain function (15 papers), Visual perception and processing mechanisms (9 papers) and Memory and Neural Mechanisms (6 papers). Xue-Xin Wei collaborates with scholars based in United States, China and Germany. Xue-Xin Wei's co-authors include Alan A. Stocker, Nikolaus Kriegeskorte, Nanthia Suthana, Michael R. Sperling, Joshua Jacobs, John F. Burke, Itzhak Fried, Alec Solway, Christoph T. Weidemann and Michael J. Kahana and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Xue-Xin Wei

28 papers receiving 898 citations

Peers

Xue-Xin Wei
Comparison fields: 5 of 91
  • Cognitive Neuroscience 772
  • Cellular and Molecular Neuroscience 228
  • Artificial Intelligence 87
  • Experimental and Cognitive Psychology 73
  • Automotive Engineering 69
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Citations per field, relative to Xue-Xin Wei
Xue-Xin Wei · 1×
Citations per year, relative to Xue-Xin Wei
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Countries citing papers authored by Xue-Xin Wei

Since Specialization
Citations

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

Fields of papers citing papers by Xue-Xin Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xue-Xin Wei. 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 Xue-Xin Wei. The network helps show where Xue-Xin Wei may publish in the future.

Co-authorship network of co-authors of Xue-Xin Wei

This figure shows the co-authorship network connecting the top 25 collaborators of Xue-Xin Wei. A scholar is included among the top collaborators of Xue-Xin Wei 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 Xue-Xin Wei. Xue-Xin Wei 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 1
2 4
3 1
4 1
5 9
6 4
7 5
8 9
9 25
10 1
11 88
12
On Path Integration of Grid Cells: Isotropic Metric, Conformal Embedding and Group Representation
1
13
A zero-inflated gamma model for post-deconvolved calcium imaging traces
1
14
Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAE
1
15
Emergence of grid-like representations by training recurrent neural networks to perform spatial localization
2
16 91
17
Efficient Neural Codes under Metabolic Constraints
4
18 212
19 332
20
Efficient coding provides a direct link between prior and likelihood in perceptual Bayesian inference
25

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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