Sho Yaida
About
In The Last Decade
Sho Yaida
19 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 47
- Nuclear and High Energy Physics 786
- Astronomy and Astrophysics 689
- Statistical and Nonlinear Physics 246
- Materials Chemistry 212
- Condensed Matter Physics 185
Countries citing papers authored by Sho Yaida
This map shows the geographic impact of Sho Yaida'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 Sho Yaida with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sho Yaida more than expected).
Fields of papers citing papers by Sho Yaida
This network shows the impact of papers produced by Sho Yaida. 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 Sho Yaida. The network helps show where Sho Yaida may publish in the future.
Co-authorship network of co-authors of Sho Yaida
This figure shows the co-authorship network connecting the top 25 collaborators of Sho Yaida. A scholar is included among the top collaborators of Sho Yaida 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 Sho Yaida. Sho Yaida is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 59 | |
| 2 | 12 | |
| 3 | Fluctuation-dissipation relations for stochastic gradient descent | 5 |
| 4 | 32 | |
| 5 | 2 | |
| 6 | 87 | |
| 7 | 29 | |
| 8 | 13 | |
| 9 | 5 | |
| 10 | 3 | |
| 11 | 15 | |
| 12 | 19 | |
| 13 | 1 | |
| 14 | 28 | |
| 15 | 55 | |
| 16 | 1 | |
| 17 | 302 | |
| 18 | Viscosity bound violation in higher derivative gravity breakdown → | 389 |
| 19 | The Principles of Deep Learning Theory: An Effective Theory Approach to Understanding Neural Networks | 7 |
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.