Phan-Minh Nguyen

726 citations
7 papers · 248 indexed · h-index 4
Topics
Stochastic Gradient Optimization Techniques (4 papers)Model Reduction and Neural Networks (3 papers)Markov Chains and Monte Carlo Methods (2 papers)
Partner nations
United StatesSingapore

In The Last Decade

Phan-Minh Nguyen

7 papers receiving 239 citations

Peers

Phan-Minh Nguyen
Comparison fields: 5 of 59
  • Artificial Intelligence 159
  • Statistical and Nonlinear Physics 78
  • Statistics and Probability 43
  • Computer Vision and Pattern Recognition 39
  • Computational Mechanics 36
Replace Nicolás García Trillos with:
Nicolás García Trillos United States
Vitaly Maiorov Israel
Abbas Mehrabian Canada
Ronit Bustin Israel
Mert Gürbüzbalaban United States
Joe Neeman United States
Varun Jog United States
Claudia Totzeck Germany
Kaizheng Wang United States
Phan-Minh Nguyen relative to Nicolás García Trillos United States Nicolás García Trillos's profile →
Citations per field
00.5×1.5×2.1×
Nicolás García Trillos · 1×
Citations per year

Countries citing papers authored by Phan-Minh Nguyen

Since Specialization
Citations

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

Fields of papers citing papers by Phan-Minh Nguyen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Phan-Minh Nguyen. 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 Phan-Minh Nguyen. The network helps show where Phan-Minh Nguyen may publish in the future.

Co-authorship network of co-authors of Phan-Minh Nguyen

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

All Works

7 of 7 papers shown
#WorkIndexed citations
1 11
2 1
3 2
4
On Random Deep Weight-Tied Autoencoders: Exact Asymptotic Analysis, Phase Transitions, and Implications to Training.
7
5 214
6 11
7 2

About Phan-Minh Nguyen

Phan-Minh Nguyen is a scholar working on Statistical and Nonlinear Physics, Statistics and Probability and Artificial Intelligence, having authored 7 papers that have together received 248 indexed citations. Recurring topics across this work include Stochastic Gradient Optimization Techniques (4 papers), Model Reduction and Neural Networks (3 papers) and Markov Chains and Monte Carlo Methods (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (78 citations), Statistics and Probability (43 citations) and Artificial Intelligence (159 citations). Phan-Minh Nguyen has collaborated with scholars based in United States and Singapore. Frequent co-authors include Andrea Montanari, Mei Song, Ping Li and Tong Wu. Their work appears in journals such as Proceedings of the National Academy of Sciences, IEEE Communications Letters and arXiv (Cornell University).

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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