Kyomin Jung
- Artificial Intelligence top 1%
- Sociology and Political Science top 2%
- Statistical and Nonlinear Physics top 1%
- Information Systems top 1%
- Computer Networks and Communications top 5%
- Co-authors
- Wei ChenSejeong KwonMeeyoung ChaYajun WangHwanhee LeeYanghoon KimSeunghyun YoonDevavrat Shah
- Topics
- Topic Modeling (32 papers)Natural Language Processing Techniques (18 papers)Multimodal Machine Learning Applications (13 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEIEEE Transactions on Pattern Analysis and Machine Intelligence
- Partner nations
- South KoreaUnited StatesHong Kong
In The Last Decade
Kyomin Jung
104 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 114
- Artificial Intelligence 925
- Sociology and Political Science 765
- Statistical and Nonlinear Physics 747
- Information Systems 556
- Computer Networks and Communications 294
Countries citing papers authored by Kyomin Jung
This map shows the geographic impact of Kyomin Jung'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 Kyomin Jung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyomin Jung more than expected).
Fields of papers citing papers by Kyomin Jung
This network shows the impact of papers produced by Kyomin Jung. 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 Kyomin Jung. The network helps show where Kyomin Jung may publish in the future.
Co-authorship network of co-authors of Kyomin Jung
This figure shows the co-authorship network connecting the top 25 collaborators of Kyomin Jung. A scholar is included among the top collaborators of Kyomin Jung 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 Kyomin Jung. Kyomin Jung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 3 | |
| 4 | 3 | |
| 5 | 3 | |
| 6 | 9 | |
| 7 | 2 | |
| 8 | 0 | |
| 9 | 2 | |
| 10 | 0 | |
| 11 | 19 | |
| 12 | Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech | 10 |
| 13 | 1 | |
| 14 | 23 | |
| 15 | 1 | |
| 16 | RESERVOIR INFLOW SIMULATION USING MIKE NAM RAINFALL-RUNOFF MODEL: CASE STUDY OF CAMERON HIGHLANDS | 3 |
| 17 | Efficient Transfer Learning Schemes for Personalized Language Modeling using Recurrent Neural Network | 9 |
| 18 | Prominent Features of Rumor Propagation in Online Social Mediabreakdown → | 544 |
| 19 | Scalable Kernel k-Means via Centroid Approximation | 3 |
| 20 | IRIE: A Scalable Influence Maximization Algorithm for Independent Cascade Model and Its Extensions | 17 |
About Kyomin Jung
Kyomin Jung is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 114 papers that have together received 2.1k indexed citations. Recurring topics across this work include Topic Modeling (32 papers), Natural Language Processing Techniques (18 papers) and Multimodal Machine Learning Applications (13 papers). The work is most often cited by research in Statistical and Nonlinear Physics (747 citations), Artificial Intelligence (925 citations) and Information Systems (556 citations). Kyomin Jung has collaborated with scholars based in South Korea, United States and Hong Kong. Frequent co-authors include Wei Chen, Sejeong Kwon, Meeyoung Cha, Yajun Wang, Hwanhee Lee, Yanghoon Kim, Seunghyun Yoon, Devavrat Shah, Sungsu Lim and Subhadeep Dey. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.