Kshitij Khare
- Statistics and Probability top 1%
- Artificial Intelligence top 10%
- Molecular Biology
- Computational Mechanics
- Applied Mathematics
- Co-authors
- James P. HobertBala RajaratnamSang‐Yun OhMalay GhoshXuan CaoGeorge MichailidisZhihua SuSaptarshi Chakraborty
- Topics
- Statistical Methods and Inference (29 papers)Bayesian Methods and Mixture Models (16 papers)Markov Chains and Monte Carlo Methods (16 papers)
- Journals
- Journal of the American Statistical AssociationJournal of the Royal Statistical Society Series B (Statistical Methodology)The Annals of Statistics
- Partner nations
- United StatesColombiaAustralia
In The Last Decade
Kshitij Khare
49 papers receiving 434 citations
Peers
Comparison fields: 5 of 79
- Statistics and Probability 283
- Artificial Intelligence 186
- Molecular Biology 64
- Computational Mechanics 30
- Applied Mathematics 22
Countries citing papers authored by Kshitij Khare
This map shows the geographic impact of Kshitij Khare'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 Kshitij Khare with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kshitij Khare more than expected).
Fields of papers citing papers by Kshitij Khare
This network shows the impact of papers produced by Kshitij Khare. 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 Kshitij Khare. The network helps show where Kshitij Khare may publish in the future.
Co-authorship network of co-authors of Kshitij Khare
This figure shows the co-authorship network connecting the top 25 collaborators of Kshitij Khare. A scholar is included among the top collaborators of Kshitij Khare 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 Kshitij Khare. Kshitij Khare is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 4 | |
| 4 | 3 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 3 | |
| 9 | 2 | |
| 10 | 21 | |
| 11 | Generalized pseudolikelihood methods for inverse covariance estimation | 3 |
| 12 | 2 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 26 | |
| 16 | 4 | |
| 17 | 4 | |
| 18 | 8 | |
| 19 | 23 | |
| 20 | Gibbs Sampling, Exponential Families and Orthogonal Polynomials. Rejoinder. | 1 |
About Kshitij Khare
Kshitij Khare is a scholar working on Statistics and Probability, Artificial Intelligence and General Economics, Econometrics and Finance, having authored 51 papers that have together received 449 indexed citations. Recurring topics across this work include Statistical Methods and Inference (29 papers), Bayesian Methods and Mixture Models (16 papers) and Markov Chains and Monte Carlo Methods (16 papers). The work is most often cited by research in Statistics and Probability (283 citations), Artificial Intelligence (186 citations) and Computational Mathematics (2 citations). Kshitij Khare has collaborated with scholars based in United States, Colombia and Australia. Frequent co-authors include James P. Hobert, Bala Rajaratnam, Sang‐Yun Oh, Malay Ghosh, Xuan Cao, George Michailidis, Zhihua Su, Saptarshi Chakraborty, Persi Diaconis and Laurent Saloff‐Coste. Their work appears in journals such as Journal of the American Statistical Association, Journal of the Royal Statistical Society Series B (Statistical Methodology) and The Annals of Statistics.
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.