Garrett B. Goh
About
In The Last Decade
Garrett B. Goh
18 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 138
- Molecular Biology 654
- Materials Chemistry 403
- Computational Theory and Mathematics 363
- Atomic and Molecular Physics, and Optics 156
- Spectroscopy 127
Countries citing papers authored by Garrett B. Goh
This map shows the geographic impact of Garrett B. Goh'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 Garrett B. Goh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Garrett B. Goh more than expected).
Fields of papers citing papers by Garrett B. Goh
This network shows the impact of papers produced by Garrett B. Goh. 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 Garrett B. Goh. The network helps show where Garrett B. Goh may publish in the future.
Co-authorship network of co-authors of Garrett B. Goh
This figure shows the co-authorship network connecting the top 25 collaborators of Garrett B. Goh. A scholar is included among the top collaborators of Garrett B. Goh 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 Garrett B. Goh. Garrett B. Goh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 32 | |
| 2 | 60 | |
| 3 | SMILES2vec: Predicting Chemical Properties from Text Representations | 9 |
| 4 | 3 | |
| 5 | ChemNet: A Transferable and Generalizable Deep Neural Network for Small-Molecule Property Prediction | 6 |
| 6 | Deep learning for computational chemistry breakdown → | 555 |
| 7 | 16 | |
| 8 | 17 | |
| 9 | 34 | |
| 10 | 36 | |
| 11 | 43 | |
| 12 | 27 | |
| 13 | 47 | |
| 14 | 78 | |
| 15 | 100 | |
| 16 | 15 | |
| 17 | 87 | |
| 18 | 22 |
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.