This map shows the geographic impact of Yingzhen Li'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 Yingzhen Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yingzhen Li more than expected).
This network shows the impact of papers produced by Yingzhen Li. 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 Yingzhen Li. The network helps show where Yingzhen Li may publish in the future.
Co-authorship network of co-authors of Yingzhen Li
This figure shows the co-authorship network connecting the top 25 collaborators of Yingzhen Li.
A scholar is included among the top collaborators of Yingzhen Li 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 Yingzhen Li. Yingzhen Li is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Li, Yingzhen, et al.. (2020). Hierarchical Sparse Variational Autoencoder for Text Encoding.. arXiv (Cornell University).1 indexed citations
9.
Foong, Andrew Y. K., David R. Burt, Yingzhen Li, & Richard E. Turner. (2020). On the Expressiveness of Approximate Inference in Bayesian Neural Networks. Neural Information Processing Systems. 33. 15897–15908.5 indexed citations
Foong, Andrew Y. K., David R. Burt, Yingzhen Li, & Richard E. Turner. (2019). Pathologies of Factorised Gaussian and MC Dropout Posteriors in Bayesian Neural Networks.. arXiv (Cornell University).5 indexed citations
12.
Li, Yingzhen & Stephan Mandt. (2018). A Deep Generative Model for Disentangled Representations of Sequential Data.. arXiv (Cornell University).3 indexed citations
13.
Li, Yingzhen, John Bradshaw, & Yash Sharma. (2018). Are Generative Classifiers More Robust to Adversarial Attacks. arXiv (Cornell University). 3804–3814.10 indexed citations
Chemmanur, Thomas J., et al.. (2017). Information Production by Institutions around CEO Turnovers and Institutional Trading as a Corporate Governance Mechanism. SSRN Electronic Journal.1 indexed citations
16.
Li, Yingzhen & Richard E. Turner. (2017). Gradient Estimators for Implicit Models. International Conference on Learning Representations.2 indexed citations
Li, Yingzhen, et al.. (2012). Geometric Construction Method of Linear SVM Multi-class Classifier. Jisuanji gongcheng.1 indexed citations
19.
Li, Yingzhen. (2011). Dynamic Relations between Foreign Trade,FDI and CO_2 Emission:An Empirical Analysis of Zhejiang Province.1 indexed citations
20.
Li, Yingzhen. (2010). Analysis of the Fluctuations of China's Import Growth:1979～2008.1 indexed citations
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.