Hsing-Hen Chen

961 citations
13 papers · 756 · h-index 10

Impact in

Papers in

Hsing-Hen Chen

13 papers receiving 702 citations

Peers

Hsing-Hen Chen
Comparison fields: 5 of 49
  • Statistical and Nonlinear Physics 470
  • Atomic and Molecular Physics, and Optics 390
  • Mathematical Physics 75
  • Nuclear and High Energy Physics 82
  • Computational Mathematics 3
Replace D. Roekaerts with:
D. Roekaerts Belgium
H. H. Chen United States
Sven Gnutzmann∥ Germany
Piotr Garbaczewski Poland
Oktay K. Pashaev Türkiye
G P Flessas United Kingdom
Natig M. Atakishiyev Mexico
N. Ja. Vilenkin Ukraine
G. S. Pogosyan Russia
C. Nash Ireland
Hsing-Hen Chen relative to D. Roekaerts Belgium D. Roekaerts's profile →
Citations per field
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D. Roekaerts · 1×
Citations per year

Countries citing papers authored by Hsing-Hen Chen

Since Specialization
Citations

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

Fields of papers citing papers by Hsing-Hen Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hsing-Hen Chen. 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 Hsing-Hen Chen. The network helps show where Hsing-Hen Chen may publish in the future.

Co-authors

The 10 scholars most cited alongside Hsing-Hen Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hsing-Hen Chen Line = papers co-authored together Hsing-Hen Chen links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 1976367
2 198071
3
Higher Order Recurrent Networks and Grammatical Inference
198968
4 198350
5 197542
6 199541
7 198141
8 197729
9
Green's Function Method for Fast On-Line Learning Algorithm of Recurrent Neural Networks
199122
10
Time Warping Invariant Neural Networks
199211
11
A Novel Net that Learns Sequential Decision Process
19876
12 19855
13 19863

About Hsing-Hen Chen

Hsing-Hen Chen is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Astronomy and Astrophysics, Atomic and Molecular Physics, and Optics and Mathematical Physics, having authored 13 papers that have together received 756 indexed citations. Recurring topics across this work include Nonlinear Waves and Solitons (5 papers), Nonlinear Photonic Systems (4 papers), Neural Networks and Applications (4 papers), Ionosphere and magnetosphere dynamics (3 papers), Laser-induced spectroscopy and plasma (2 papers), Machine Learning and Algorithms (2 papers), Advanced Mathematical Physics Problems (2 papers) and Model Reduction and Neural Networks (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (470 citations), Atomic and Molecular Physics, and Optics (390 citations), Mathematical Physics (75 citations), Nuclear and High Energy Physics (82 citations) and Computational Mathematics (3 citations). Hsing-Hen Chen has collaborated with scholars based in United States. Frequent co-authors include Chuan-Sheng Liu, Akira Nakamura, Guo-Zheng Sun, Dong Chen, C. Lee Giles, Celso Grebogi, V. K. Tripathi, Mark W. Goudreau, Y. C. Lee and Curtis R. Menyuk. Their work appears in journals such as Physical Review Letters, Journal of the Physical Society of Japan, Journal of Mathematical Physics, The Physics of Fluids and IEEE Transactions on Neural Networks.

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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