Andrew Moore
About
In The Last Decade
Andrew Moore
144 papers receiving 15.0k citations
Hit Papers
Peers
Comparison fields: 5 of 219
- Artificial Intelligence 8.6k
- Computer Vision and Pattern Recognition 2.8k
- Computer Networks and Communications 2.1k
- Control and Systems Engineering 2.1k
- Computational Theory and Mathematics 1.5k
Countries citing papers authored by Andrew Moore
This map shows the geographic impact of Andrew Moore'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 Andrew Moore with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Moore more than expected).
Fields of papers citing papers by Andrew Moore
This network shows the impact of papers produced by Andrew Moore. 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 Andrew Moore. The network helps show where Andrew Moore may publish in the future.
Co-authorship network of co-authors of Andrew Moore
This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Moore. A scholar is included among the top collaborators of Andrew Moore 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 Andrew Moore. Andrew Moore is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 26 | |
| 4 | Fast State Discovery for HMM Model Selection and Learning | 29 |
| 5 | Monitoring food safety by detecting patterns in consumer complaints | 2 |
| 6 | Detecting Significant Multidimensional Spatial Clusters | 37 |
| 7 | Active Learning for Anomaly and Rare-Category Detection | 92 |
| 8 | Bayesian network anomaly pattern detection for disease outbreaks | 104 |
| 9 | Rapid Evaluation of Multiple Density Models. | 43 |
| 10 | A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters | 31 |
| 11 | Efficient exact k-NN and nonparametric classification in high dimensions | 32 |
| 12 | Another wild colonial boy?: Francis de Groot and the Harbour Bridge | 1 |
| 13 | Using Tarjan's Red Rule for Fast Dependency Tree Construction | 7 |
| 14 | Interpolating conditional density trees | 4 |
| 15 | `N-Body' Problems in Statistical Learning | 167 |
| 16 | 'History without facts': M. H. Ellis, Manning Clark and the origins of the Australian Dictionary of Biography | 1 |
| 17 | Barycentric Interpolators for Continuous Space and Time Reinforcement Learning | 21 |
| 18 | Learning evaluation functions for global optimization and Boolean satisfiability | 47 |
| 19 | Generalization in Reinforcement Learning: Safely Approximating the Value Function | 326 |
| 20 | Memory-Based Methods for Regression and Classification | 9 |
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.