Quan Hung Tran

758 total citations
26 papers, 427 citations indexed

About

Quan Hung Tran is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Quan Hung Tran has authored 26 papers receiving a total of 427 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 3 papers in Information Systems. Recurrent topics in Quan Hung Tran's work include Topic Modeling (18 papers), Natural Language Processing Techniques (17 papers) and Speech and dialogue systems (6 papers). Quan Hung Tran is often cited by papers focused on Topic Modeling (18 papers), Natural Language Processing Techniques (17 papers) and Speech and dialogue systems (6 papers). Quan Hung Tran collaborates with scholars based in United States, Australia and Vietnam. Quan Hung Tran's co-authors include Tuan Lai, Dinh Phung, Trung Le, Trung Bui, Gholamreza Haffari, Ingrid Zukerman, Heng Ji, ChengXiang Zhai, Van Nguyen and Dai Quoc Nguyen and has published in prestigious journals such as 2021 IEEE/CVF International Conference on Computer Vision (ICCV), Monash University Research Portal (Monash University) and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.

In The Last Decade

Quan Hung Tran

25 papers receiving 410 citations

Peers

Quan Hung Tran
Comparison fields: 5 of 41
  • Artificial Intelligence 345
  • Information Systems 118
  • Computer Vision and Pattern Recognition 80
  • Signal Processing 51
  • Molecular Biology 32
Replace Ruotian Ma with:
Ruotian Ma China
Yuxian Gu China
Panupong Pasupat United States
Carlos R. Rivero United States
Dai Quoc Nguyen Vietnam
Muyun Yang China
Luciano Del Corro Germany
Pradeep Dasigi United States
Yashoteja Prabhu India
Ruotian Ma China View profile →
Citations per field, relative to Quan Hung Tran
Quan Hung Tran · 1×
Citations per year, relative to Quan Hung Tran
Quan Hung Tran · 1×

Countries citing papers authored by Quan Hung Tran

Since Specialization
Citations

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

Fields of papers citing papers by Quan Hung Tran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Quan Hung Tran. 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 Quan Hung Tran. The network helps show where Quan Hung Tran may publish in the future.

Co-authorship network of co-authors of Quan Hung Tran

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 5
3 6
4 2
5 1
6 50
7
MOST: Multi-Source Domain Adaptation via Optimal Transport for Student-Teacher Learning
10
8 42
9 25
10 20
11 32
12 47
13 18
14
A Pointer Network Architecture for Context-Dependent Semantic Parsing
1
15 22
16 14
17 6
18 5
19 49
20 2

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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