Tomohiro Sonobe
Impact in
- Artificial Intelligence top 2%
- Quantum Computing Algorithms and Architecture
- Neural Networks and Reservoir Computing
- Quantum Information and Cryptography
- Advanced Graph Neural Networks
Papers in
-
- Constraint Satisfaction and Optimization 6
-
- Complex Network Analysis Techniques 5
- Co-authors
- Ken‐ichi Kawarabayashi (6 shared papers)Koji Enbutsu (2 shared papers)Takeshi Umeki (2 shared papers)Takahiro Inagaki (2 shared papers)Hiroki Takesue (2 shared papers)Toshimori Honjo (2 shared papers)Kazuyuki Aihara (1 shared paper)Peter L. McMahon (1 shared paper)
- Journals
- Science (1 paper)Science Advances (1 paper)Physical review. E (1 paper)Lecture notes in computer science (5 papers)International Conference on Machine Learning (1 paper)
- Partner nations
- JapanUnited States
In The Last Decade
Tomohiro Sonobe
11 papers receiving 1.0k citations
Tomohiro Sonobe's Hit Papers
Peers
Comparison fields: 5 of 59
- Artificial Intelligence 855
- Acoustics and Ultrasonics 9
- Computational Theory and Mathematics 149
- Statistical and Nonlinear Physics 94
- Electrical and Electronic Engineering 318
Countries citing papers authored by Tomohiro Sonobe
This map shows the geographic impact of Tomohiro Sonobe'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 Tomohiro Sonobe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tomohiro Sonobe more than expected).
Fields of papers citing papers by Tomohiro Sonobe
This network shows the impact of papers produced by Tomohiro Sonobe. 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 Tomohiro Sonobe. The network helps show where Tomohiro Sonobe may publish in the future.
Co-authors
The 25 scholars most cited alongside Tomohiro Sonobe, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | A coherent Ising machine for 2000-node optimization problems Hit paper breakdown → | 2016 | 555 |
| 2 | 100,000-spin coherent Ising machine Hit paper breakdown → | 2021 | 237 |
| 3 | Representation Learning on Graphs with Jumping Knowledge Networks | 2018 | 151 |
| 4 | 2019 | 71 | |
| 5 | 2017 | 26 | |
| 6 | 2018 | 10 | |
| 7 | 2014 | 10 | |
| 8 | 2012 | 5 | |
| 9 | 2013 | 3 | |
| 10 | 2018 | 1 | |
| 11 | 2022 | 1 | |
| 12 | 2016 | 0 | |
| 13 | 2023 | 0 |
About Tomohiro Sonobe
Tomohiro Sonobe is a scholar working on Computer Networks and Communications, Statistical and Nonlinear Physics, Artificial Intelligence, Computational Theory and Mathematics and Industrial and Manufacturing Engineering, having authored 13 papers that have together received 1.1k indexed citations. Recurring topics across this work include Constraint Satisfaction and Optimization (6 papers), Complex Network Analysis Techniques (5 papers), Formal Methods in Verification (4 papers), Scheduling and Optimization Algorithms (3 papers), Quantum Computing Algorithms and Architecture (3 papers), Quantum Information and Cryptography (2 papers), Logic, programming, and type systems (2 papers) and Advanced Graph Neural Networks (2 papers). The work is most often cited by research in Artificial Intelligence (855 citations), Acoustics and Ultrasonics (9 citations), Computational Theory and Mathematics (149 citations), Statistical and Nonlinear Physics (94 citations) and Electrical and Electronic Engineering (318 citations). Tomohiro Sonobe has collaborated with scholars based in Japan and United States. Frequent co-authors include Ken‐ichi Kawarabayashi, Koji Enbutsu, Takeshi Umeki, Takahiro Inagaki, Hiroki Takesue, Toshimori Honjo, Kazuyuki Aihara, Peter L. McMahon, Yoshitaka Haribara and Shuhei Tamate. Their work appears in journals such as Science, Science Advances, Physical review. E, Lecture notes in computer science and International Conference on Machine Learning.
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.