Richard D. Lawrence
- Artificial Intelligence top 2%
- Information Systems top 2%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 10%
- Marketing top 5%
- Co-authors
- Prem MelvilleWojciech GrycGeorge AlmásiJingrui HeVladimir KotlyarSastry DuriMarisa ViverosHolly Rushmeier
- Topics
- Text and Document Classification Technologies (8 papers)Machine Learning and Algorithms (5 papers)Image Retrieval and Classification Techniques (4 papers)
- Journals
- The LancetChemical Research in ToxicologySAE technical papers on CD-ROM/SAE technical paper series
- Partner nations
- United StatesIsraelUnited Kingdom
In The Last Decade
Richard D. Lawrence
45 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 138
- Artificial Intelligence 677
- Information Systems 334
- Computer Vision and Pattern Recognition 191
- Computer Networks and Communications 162
- Marketing 111
Countries citing papers authored by Richard D. Lawrence
This map shows the geographic impact of Richard D. Lawrence'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 Richard D. Lawrence with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard D. Lawrence more than expected).
Fields of papers citing papers by Richard D. Lawrence
This network shows the impact of papers produced by Richard D. Lawrence. 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 Richard D. Lawrence. The network helps show where Richard D. Lawrence may publish in the future.
Co-authorship network of co-authors of Richard D. Lawrence
This figure shows the co-authorship network connecting the top 25 collaborators of Richard D. Lawrence. A scholar is included among the top collaborators of Richard D. Lawrence 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 Richard D. Lawrence. Richard D. Lawrence is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 27 | |
| 2 | MILEAGE: Multiple Instance LEArning with Global Embedding | 11 |
| 3 | 4 | |
| 4 | 5 | |
| 5 | Multiple Instance Learning on Structured Data | 30 |
| 6 | 15 | |
| 7 | 4 | |
| 8 | 17 | |
| 9 | 15 | |
| 10 | 39 | |
| 11 | 34 | |
| 12 | 18 | |
| 13 | Running Massively Multiplayer Games as a Business. | 3 |
| 14 | 110 | |
| 15 | 6 | |
| 16 | 11 | |
| 17 | Amygdalin toxicity studies in rats predict chronic cyanide poisoning in humans. | 43 |
| 18 | 4 | |
| 19 | A study of quasi-analytic models for improvement of the military commander's tactical decision process / | 1 |
| 20 | 1 |
About Richard D. Lawrence
Richard D. Lawrence is a scholar working on Computational Mathematics, Artificial Intelligence and Hardware and Architecture, having authored 45 papers that have together received 1.4k indexed citations. Recurring topics across this work include Text and Document Classification Technologies (8 papers), Machine Learning and Algorithms (5 papers) and Image Retrieval and Classification Techniques (4 papers). The work is most often cited by research in Artificial Intelligence (677 citations), Computer Science Applications (100 citations) and Hardware and Architecture (101 citations). Richard D. Lawrence has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Prem Melville, Wojciech Gryc, George Almási, Jingrui He, Vladimir Kotlyar, Sastry Duri, Marisa Viveros, Holly Rushmeier, Yan Liu and Dan Zhang. Their work appears in journals such as The Lancet, Chemical Research in Toxicology and SAE technical papers on CD-ROM/SAE technical paper series.
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.