Mary Phuong

17 total papers · 1.3k total citations
6 papers, 152 citations indexed

About

Mary Phuong is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mary Phuong has authored 6 papers receiving a total of 152 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 2 papers in Statistical and Nonlinear Physics and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in Mary Phuong's work include Neural Networks and Applications (2 papers), Model Reduction and Neural Networks (2 papers) and Machine Learning and Data Classification (2 papers). Mary Phuong is often cited by papers focused on Neural Networks and Applications (2 papers), Model Reduction and Neural Networks (2 papers) and Machine Learning and Data Classification (2 papers). Mary Phuong collaborates with scholars based in Austria, Slovakia and Netherlands. Mary Phuong's co-authors include Christoph H. Lampert, Nate Kushman, Sebastian Nowozin, Ryota Tomioka, Max Welling and Anna Krakovská and has published in prestigious journals such as Measurement Science Review, arXiv (Cornell University) and International Conference on Learning Representations.

In The Last Decade

Mary Phuong

5 papers receiving 151 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Mary Phuong	110	76	16	12	9	6	152
Jinmian Ye	91 0.8×	79 1.0×	12 0.8×	17 1.4×	13 1.4×	7	160
Suraj Srinivas	112 1.0×	91 1.2×	7 0.4×	12 1.0×	9 1.0×	10	165
Danlu Chen	100 0.9×	138 1.8×	13 0.8×	17 1.4×	7 0.8×	3	188
Jiefeng Peng	119 1.1×	150 2.0×	9 0.6×	17 1.4×	10 1.1×	7	201
Shukang Yin	93 0.8×	56 0.7×	12 0.8×	7 0.6×	7 0.8×	6	204
Leonard Lausen	61 0.6×	50 0.7×	8 0.5×	9 0.8×	7 0.8×	5	126
Linjun Zhou	166 1.5×	101 1.3×	10 0.6×	7 0.6×	11 1.2×	7	234
Tiago S. Nazaré	51 0.5×	86 1.1×	11 0.7×	13 1.1×	6 0.7×	7	144
Huangjie Zheng	86 0.8×	77 1.0×	13 0.8×	9 0.8×	10 1.1×	10	170
Yunzhong Hou	67 0.6×	122 1.6×	36 2.3×	18 1.5×	4 0.4×	10	176

Countries citing papers authored by Mary Phuong

Since Specialization

Citations

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

Fields of papers citing papers by Mary Phuong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mary Phuong

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

All Works

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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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