Edward I. George
About
In The Last Decade
Edward I. George
107 papers receiving 8.5k citations
Hit Papers
Peers
Comparison fields: 5 of 206
- Statistics and Probability 4.0k
- Artificial Intelligence 2.8k
- Economics and Econometrics 1.3k
- Management Science and Operations Research 962
- Molecular Biology 737
Countries citing papers authored by Edward I. George
This map shows the geographic impact of Edward I. George'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 Edward I. George with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edward I. George more than expected).
Fields of papers citing papers by Edward I. George
This network shows the impact of papers produced by Edward I. George. 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 Edward I. George. The network helps show where Edward I. George may publish in the future.
Co-authorship network of co-authors of Edward I. George
This figure shows the co-authorship network connecting the top 25 collaborators of Edward I. George. A scholar is included among the top collaborators of Edward I. George 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 Edward I. George. Edward I. George is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 33 | |
| 2 | On variance estimation for Bayesian variable selection | 2 |
| 3 | Determinantal Regularization for Ensemble Variable Selection | 3 |
| 4 | Models as Approximations - A Conspiracy of Random Regressors and Model Deviations Against Classical Inference in Regression | 4 |
| 5 | The Conspiracy of Random Predictors and Model Violations against Classical Inference in Regression | 3 |
| 6 | 22 | |
| 7 | Models as Approximations, Part I: A Conspiracy of Nonlinearity and Random Regressors in Linear Regression | 8 |
| 8 | 84 | |
| 9 | 19 | |
| 10 | Variable Selection Inference for Bayesian Additive Regression Trees | 3 |
| 11 | Covariance Based Pre-Filters and Screening Criteria for Conjunction Analysis | 2 |
| 12 | A g-prior extension for p>n | 2 |
| 13 | 5 | |
| 14 | 9 | |
| 15 | Managing Multiple Models. | 7 |
| 16 | A bayesian model for collaborative filtering. | 88 |
| 17 | APPROACHES FOR BAYESIAN VARIABLE SELECTION breakdown → | 750 |
| 18 | Variable Selection via Gibbs Sampling breakdown → | 1745 |
| 19 | Explaining the Gibbs Sampler breakdown → | 1605 |
| 20 | 96 |
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.