Yeming Wen

834 total citations
5 papers, 54 citations indexed

About

Yeming Wen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Mechanics. According to data from OpenAlex, Yeming Wen has authored 5 papers receiving a total of 54 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Computational Mechanics. Recurrent topics in Yeming Wen's work include Advanced Neural Network Applications (3 papers), Sparse and Compressive Sensing Techniques (2 papers) and Stochastic Gradient Optimization Techniques (2 papers). Yeming Wen is often cited by papers focused on Advanced Neural Network Applications (3 papers), Sparse and Compressive Sensing Techniques (2 papers) and Stochastic Gradient Optimization Techniques (2 papers). Yeming Wen collaborates with scholars based in Canada and United States. Yeming Wen's co-authors include Jimmy Ba, Dustin Tran, Michele Catasta, Harris Chan, Pengcheng Yin, Henryk Michalewski, Guodong Zhang, Roger Grosse, Kefan Xiao and J. J. Howland and has published in prestigious journals such as arXiv (Cornell University) and International Conference on Artificial Intelligence and Statistics.

In The Last Decade

Yeming Wen

5 papers receiving 52 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Yeming Wen Canada	4	38	19	6	4	3	5	54
Emilie Morvant France	6	55 1.4×	18 0.9×	4 0.7×	6 1.5×	2 0.7×	10	69
Prakash Dey India	4	42 1.1×	30 1.6×	4 0.7×	8 2.0×		8	49
Edward Lockhart United Kingdom	3	44 1.2×	8 0.4×	6 1.0×	3 0.8×		4	57
I. Babuschkin United States	3	45 1.2×	16 0.8×	5 0.8×	1 0.3×	3 1.0×	6	66
Edward De Brouwer Belgium	5	34 0.9×	7 0.4×	3 0.5×	8 2.0×	1 0.3×	10	51
Sumith Kulal United States	4	21 0.6×	18 0.9×	8 1.3×	3 0.8×	3 1.0×	7	43
Karan Goel United States	4	21 0.6×	9 0.5×	3 0.5×	4 1.0×		10	34
Luoxin Chen United States	4	47 1.2×	9 0.5×	3 0.5×	3 0.8×		5	56
Souradyuti Paul India	4	30 0.8×	23 1.2×	2 0.3×	3 0.8×		11	35
Thomas Wolf United States	4	54 1.4×	26 1.4×	9 1.5×	3 0.8×		8	76

Countries citing papers authored by Yeming Wen

Since Specialization

Citations

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

Fields of papers citing papers by Yeming Wen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yeming Wen

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

All Works

Sort: Min cites: Since: Top N: Style:

5 of 5 papers shown

1.

Yin, Pengcheng, Kefan Xiao, Abhishek S. Rao, et al.. (2023). Natural Language to Code Generation in Interactive Data Science Notebooks. 126–173. 7 indexed citations

2.

Wen, Yeming, et al.. (2020). An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise. International Conference on Artificial Intelligence and Statistics. 3621–3631. 1 indexed citations

3.

Wen, Yeming, Dustin Tran, & Jimmy Ba. (2020). BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning. arXiv (Cornell University). 33 indexed citations

4.

Wen, Yeming, et al.. (2019). Interplay Between Optimization and Generalization of Stochastic Gradient Descent with Covariance Noise.. arXiv (Cornell University). 7 indexed citations

5.

Wen, Yeming, Paul Vicol, Jimmy Ba, Dustin Tran, & Roger Grosse. (2018). Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. arXiv (Cornell University). 6 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.

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