Yukito Iba
- Molecular Biology
- Condensed Matter Physics top 10%
- Materials Chemistry
- Statistical and Nonlinear Physics top 10%
- Artificial Intelligence
- Co-authors
- Macoto KikuchiGeorge ChikenjiKoji HukushimaNen SaitoKazuyuki AiharaShotaro AkahoToshio AoyagiKen Nakae
- Topics
- Theoretical and Computational Physics (10 papers)Neural Networks and Applications (5 papers)Stochastic processes and statistical mechanics (4 papers)
- Partner nations
- JapanUnited States
In The Last Decade
Yukito Iba
22 papers receiving 356 citations
Peers
Comparison fields: 5 of 70
- Molecular Biology 157
- Condensed Matter Physics 123
- Materials Chemistry 91
- Statistical and Nonlinear Physics 68
- Artificial Intelligence 63
Countries citing papers authored by Yukito Iba
This map shows the geographic impact of Yukito Iba'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 Yukito Iba with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yukito Iba more than expected).
Fields of papers citing papers by Yukito Iba
This network shows the impact of papers produced by Yukito Iba. 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 Yukito Iba. The network helps show where Yukito Iba may publish in the future.
Co-authorship network of co-authors of Yukito Iba
This figure shows the co-authorship network connecting the top 25 collaborators of Yukito Iba. A scholar is included among the top collaborators of Yukito Iba 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 Yukito Iba. Yukito Iba is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Backward Simulation of Stochastic Process Using a Time Reverse Monte Carlo Method | 0 |
| 2 | 0 | |
| 3 | 11 | |
| 4 | 13 | |
| 5 | 7 | |
| 6 | 4 | |
| 7 | 8 | |
| 8 | 5 | |
| 9 | 9 | |
| 10 | 11 | |
| 11 | 1 | |
| 12 | Detecting Hidden Synchronization of Chaotic Dynamical Systems: A Kernel-based Approach | 2 |
| 13 | 1 | |
| 14 | 1 | |
| 15 | Population-based Monte Carlo algorithms | 10 |
| 16 | 2 | |
| 17 | 1 | |
| 18 | 66 | |
| 19 | 5 | |
| 20 | 57 |
About Yukito Iba
Yukito Iba is a scholar working on Statistics and Probability, Statistical and Nonlinear Physics and Condensed Matter Physics, having authored 25 papers that have together received 374 indexed citations. Recurring topics across this work include Theoretical and Computational Physics (10 papers), Neural Networks and Applications (5 papers) and Stochastic processes and statistical mechanics (4 papers). The work is most often cited by research in Condensed Matter Physics (123 citations), Statistical and Nonlinear Physics (68 citations) and Statistics and Probability (45 citations). Yukito Iba has collaborated with scholars based in Japan and United States. Frequent co-authors include Macoto Kikuchi, George Chikenji, Koji Hukushima, Nen Saito, Kazuyuki Aihara, Shotaro Akaho, Toshio Aoyagi, Ken Nakae, Yasuhiro Tsubo and Tomoki Fukai. Their work appears in journals such as Physical Review Letters, Computer Physics Communications and Neural Computation.
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.