Anqi Wu

852 total citations
39 papers, 415 citations indexed

About

Anqi Wu is a scholar working on Molecular Biology, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Anqi Wu has authored 39 papers receiving a total of 415 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 9 papers in Artificial Intelligence and 8 papers in Cognitive Neuroscience. Recurrent topics in Anqi Wu's work include Gaussian Processes and Bayesian Inference (5 papers), Neural dynamics and brain function (4 papers) and Ferroptosis and cancer prognosis (3 papers). Anqi Wu is often cited by papers focused on Gaussian Processes and Bayesian Inference (5 papers), Neural dynamics and brain function (4 papers) and Ferroptosis and cancer prognosis (3 papers). Anqi Wu collaborates with scholars based in China, United States and Netherlands. Anqi Wu's co-authors include Jonathan W. Pillow, Xiao Yu, Daren Yu, Qinghua Hu, Jinfu Liu, Nicholas Roy, Peng Wang, Jeffrey T. Koberstein, Feng Pan and N. J. TURRO and has published in prestigious journals such as SHILAP Revista de lepidopterología, NeuroImage and Langmuir.

In The Last Decade

Anqi Wu

34 papers receiving 409 citations

Peers

Anqi Wu
Comparison fields: 5 of 107
  • Artificial Intelligence 98
  • Biomedical Engineering 98
  • Cognitive Neuroscience 86
  • Molecular Biology 64
  • Signal Processing 57
Replace Hongwei Wei with:
Hongwei Wei China
Chunnan Wang China
Abdulaziz Al‐Ali Qatar
Yingfei Sun China
Woojoo Lee South Korea
Muhammad Obaid Ullah Pakistan
Zhixian Chen China
Pingping Zhang China
Yihan Lin China
Hongwei Wei China View profile →
Citations per field, relative to Anqi Wu
Anqi Wu · 1×
Citations per year, relative to Anqi Wu
Anqi Wu · 1×

Countries citing papers authored by Anqi Wu

Since Specialization
Citations

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

Fields of papers citing papers by Anqi Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anqi Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Anqi Wu. A scholar is included among the top collaborators of Anqi Wu 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 Anqi Wu. Anqi Wu 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 0
3 5
4 14
5 4
6 5
7 8
8 32
9 16
10 1
11
Differentiated Prosodic Adaption of Chinese and English Poetry: An Acoustic Approach to Reading of Chinese Tang Poetry and Shakespearean Sonnets
1
12
Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking
2
13 5
14
Dependent relevance determination for smooth and structured sparse regression
3
15
Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks
4
16 12
17
Fixing Variational Bayes: Deterministic Variational Inference for Bayesian Neural Networks
4
18
Learning a latent manifold of odor representations from neural responses in piriform cortex
7
19
Convolutional spike-triggered covariance analysis for neural subunit models
8
20
Sparse Bayesian Structure Learning with Dependent Relevance Determination Priors
5

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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