Scott Davies
- Artificial Intelligence top 5%
- Computational Theory and Mathematics top 5%
- Industrial and Manufacturing Engineering top 10%
- Computer Networks and Communications
- Molecular Biology
- Co-authors
- Shumeet BalujaStuart RussellAndrew MooreAndrew Y. NgD.N. SwinglerBrigham AndersonPaul KomarekJeff Schneider
- Topics
- Bayesian Modeling and Causal Inference (6 papers)Data Management and Algorithms (5 papers)Time Series Analysis and Forecasting (3 papers)
- Cited by
- Artificial IntelligenceComputational Theory and MathematicsIndustrial and Manufacturing Engineering
- Journals
- arXiv (Cornell University)Neural Information Processing SystemsInternational Conference on Machine Learning
- Partner nations
- United StatesCanada
In The Last Decade
Scott Davies
12 papers receiving 438 citations
Peers
Comparison fields: 5 of 66
- Artificial Intelligence 362
- Computational Theory and Mathematics 109
- Industrial and Manufacturing Engineering 55
- Computer Networks and Communications 48
- Molecular Biology 46
Countries citing papers authored by Scott Davies
This map shows the geographic impact of Scott Davies'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 Scott Davies with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Scott Davies more than expected).
Fields of papers citing papers by Scott Davies
This network shows the impact of papers produced by Scott Davies. 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 Scott Davies. The network helps show where Scott Davies may publish in the future.
Co-authorship network of co-authors of Scott Davies
This figure shows the co-authorship network connecting the top 25 collaborators of Scott Davies. A scholar is included among the top collaborators of Scott Davies 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 Scott Davies. Scott Davies is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 7 | |
| 3 | Interpolating conditional density trees | 4 |
| 4 | Fast factored density estimation and compression with bayesian networks | 6 |
| 5 | 1 | |
| 6 | 18 | |
| 7 | Applying Online Search Techniques to Continuous-State Reinforcement Learning | 7 |
| 8 | Fast probabilistic modeling for combinatorial optimization | 65 |
| 9 | Using Optimal Dependency-Trees for Combinational Optimization | 88 |
| 10 | Using Optimal Dependency-Trees for Combinatorial Optimization: Learning the Structure of the Search Space | 172 |
| 11 | Combining Multiple Optimization Runs with Optimal Dependency Trees | 21 |
| 12 | Multidimensional Triangulation and Interpolation for Reinforcement Learning | 37 |
| 13 | NP-Completeness of Searches for Smallest Possible Feature Sets | 66 |
About Scott Davies
Scott Davies is a scholar working on Signal Processing, Artificial Intelligence and Computer Networks and Communications, having authored 13 papers that have together received 492 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (6 papers), Data Management and Algorithms (5 papers) and Time Series Analysis and Forecasting (3 papers). The work is most often cited by research in Artificial Intelligence (362 citations), Computational Theory and Mathematics (109 citations) and Industrial and Manufacturing Engineering (55 citations). Scott Davies has collaborated with scholars based in United States and Canada. Frequent co-authors include Shumeet Baluja, Stuart Russell, Andrew Moore, Andrew Y. Ng, D.N. Swingler, Brigham Anderson, Paul Komarek, Jeff Schneider, Rémi Munos and Andrew W. Moore. Their work appears in journals such as arXiv (Cornell University), Neural Information Processing Systems and International Conference on Machine Learning.
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.