Pradeep Ravikumar
- Statistics and Probability top 1%
- Artificial Intelligence top 5%
- Computational Mechanics top 5%
- Molecular Biology
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Martin J. WainwrightGarvesh RaskuttiBin YuHan LiuJohn LaffertyLarry WassermanEunho YangAmbuj Tewari
- Topics
- Statistical Methods and Inference (5 papers)Bayesian Modeling and Causal Inference (3 papers)Machine Learning and Algorithms (3 papers)
- Journals
- Journal of the Royal Statistical Society Series B (Statistical Methodology)Inverse ProblemsBMC Systems Biology
- Partner nations
- United StatesSwedenSouth Korea
In The Last Decade
Pradeep Ravikumar
17 papers receiving 812 citations
Peers
Comparison fields: 5 of 90
- Statistics and Probability 454
- Artificial Intelligence 359
- Computational Mechanics 178
- Molecular Biology 122
- Computer Vision and Pattern Recognition 80
Countries citing papers authored by Pradeep Ravikumar
This map shows the geographic impact of Pradeep Ravikumar'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 Pradeep Ravikumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pradeep Ravikumar more than expected).
Fields of papers citing papers by Pradeep Ravikumar
This network shows the impact of papers produced by Pradeep Ravikumar. 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 Pradeep Ravikumar. The network helps show where Pradeep Ravikumar may publish in the future.
Co-authorship network of co-authors of Pradeep Ravikumar
This figure shows the co-authorship network connecting the top 25 collaborators of Pradeep Ravikumar. A scholar is included among the top collaborators of Pradeep Ravikumar 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 Pradeep Ravikumar. Pradeep Ravikumar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Context-Sensitive Spelling Correction of Clinical Text via Conditional Independence. | 2 |
| 2 | Improved Clinical Abbreviation Expansion via Non-Sense-Based Approaches | 4 |
| 3 | DAGs with NO TEARS: Smooth Optimization for Structure Learning. | 1 |
| 4 | 3 | |
| 5 | 13 | |
| 6 | 11 | |
| 7 | A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models | 3 |
| 8 | Tracking with ranked signals | 1 |
| 9 | 9 | |
| 10 | 21 | |
| 11 | Elementary Estimators for Sparse Covariance Matrices and other Structured Moments | 10 |
| 12 | Human Boosting | 1 |
| 13 | Regularized sparse inverse covariance matrix estimation | 2 |
| 14 | On NDCG Consistency of Listwise Ranking Methods | 39 |
| 15 | On Learning Discrete Graphical Models using Group-Sparse Regularization | 29 |
| 16 | 392 | |
| 17 | 305 |
About Pradeep Ravikumar
Pradeep Ravikumar is a scholar working on Statistics and Probability, Artificial Intelligence and Signal Processing, having authored 17 papers that have together received 846 indexed citations. Recurring topics across this work include Statistical Methods and Inference (5 papers), Bayesian Modeling and Causal Inference (3 papers) and Machine Learning and Algorithms (3 papers). The work is most often cited by research in Statistics and Probability (454 citations), Computational Mathematics (8 citations) and Artificial Intelligence (359 citations). Pradeep Ravikumar has collaborated with scholars based in United States, Sweden and South Korea. Frequent co-authors include Martin J. Wainwright, Garvesh Raskutti, Bin Yu, Han Liu, John Lafferty, Larry Wasserman, Eunho Yang, Ambuj Tewari, Ali Jalali and Sujay Sanghavi. Their work appears in journals such as Journal of the Royal Statistical Society Series B (Statistical Methodology), Inverse Problems and BMC Systems Biology.
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.