This map shows the geographic impact of Yunchen Pu'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 Yunchen Pu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yunchen Pu more than expected).
This network shows the impact of papers produced by Yunchen Pu. 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 Yunchen Pu. The network helps show where Yunchen Pu may publish in the future.
Co-authorship network of co-authors of Yunchen Pu
This figure shows the co-authorship network connecting the top 25 collaborators of Yunchen Pu.
A scholar is included among the top collaborators of Yunchen Pu 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 Yunchen Pu. Yunchen Pu is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Chen, Li‐Qun, Shuyang Dai, Yunchen Pu, et al.. (2018). Symmetric Variational Autoencoder and Connections to Adversarial Learning. International Conference on Artificial Intelligence and Statistics. 661–669.12 indexed citations
4.
Pu, Yunchen, Shuyang Dai, Zhe Gan, et al.. (2018). JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets. International Conference on Machine Learning. 4151–4160.3 indexed citations
Chen, Changyou, Chunyuan Li, Li‐Qun Chen, et al.. (2017). Continuous-Time Flows for Deep Generative Models.1 indexed citations
15.
Pu, Yunchen, Martin Renqiang Min, Zhe Gan, & Lawrence Carin. (2016). Adaptive Feature Abstraction for Translating Video to Language. arXiv (Cornell University).1 indexed citations
16.
Gan, Zhe, Yunchen Pu, Ricardo Henao, et al.. (2016). Unsupervised Learning of Sentence Representations using Convolutional Neural Networks. arXiv (Cornell University).3 indexed citations
Pu, Yunchen, Xin Yuan, Andrew Stevens, Chunyuan Li, & Lawrence Carin. (2015). A Deep Generative Deconvolutional Image Model. Journal of Machine Learning Research. 51. 741–750.1 indexed citations
19.
Pu, Yunchen, Xin Yuan, & Lawrence Carin. (2015). A generative model for deep convolutional learning. International Conference on Learning Representations.4 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.