Kurt De Grave
About
In The Last Decade
Kurt De Grave
12 papers receiving 276 citations
Peers
Comparison fields: 5 of 76
- Artificial Intelligence 112
- Molecular Biology 88
- Computational Theory and Mathematics 61
- Biomedical Engineering 51
- Materials Chemistry 41
Countries citing papers authored by Kurt De Grave
This map shows the geographic impact of Kurt De Grave'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 Kurt De Grave with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kurt De Grave more than expected).
Fields of papers citing papers by Kurt De Grave
This network shows the impact of papers produced by Kurt De Grave. 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 Kurt De Grave. The network helps show where Kurt De Grave may publish in the future.
Co-authorship network of co-authors of Kurt De Grave
This figure shows the co-authorship network connecting the top 25 collaborators of Kurt De Grave. A scholar is included among the top collaborators of Kurt De Grave 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 Kurt De Grave. Kurt De Grave is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Eve: Integration of machine learning with compound testing in a robot scientist | 1 |
| 2 | MIPS: A graph mining library | 0 |
| 3 | 94 | |
| 4 | 26 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | The Essential Knuth | 1 |
| 8 | The Dawn of Software Engineering: from Turing to Dijkstra | 8 |
| 9 | Pluralism in Software Engineering: Turing Award Winner Peter Naur Explains | 6 |
| 10 | Predictive Quantitative Structure-Activity Relationship Models and their use for the Efficient Screening of Molecules (Automatisch leren van structuur-activiteitsrelaties met hoge voorspellende kracht en hun toepassing bij het efficiënt screenen van moleculen) | 1 |
| 11 | Fast Neighborhood Subgraph Pairwise Distance Kernel | 107 |
| 12 | 8 | |
| 13 | 36 | |
| 14 | Active learning for primary drug screening | 3 |
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.