Krishna B. Athreya
- Mathematical Physics top 0.2%
- Statistics and Probability top 0.2%
- Artificial Intelligence top 2%
- Management Science and Operations Research top 0.5%
- Finance top 1%
- Co-authors
- Peter NeySamuel KarlinSastry G. PantulaPeter JagersDavid McDonaldN. KaplanJayaram SethuramanHani Doss
- Topics
- Stochastic processes and statistical mechanics (73 papers)Markov Chains and Monte Carlo Methods (48 papers)Bayesian Methods and Mixture Models (24 papers)
- Partner nations
- United StatesIndiaSouth Korea
In The Last Decade
Krishna B. Athreya
126 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 146
- Mathematical Physics 2.1k
- Statistics and Probability 1.5k
- Artificial Intelligence 728
- Management Science and Operations Research 699
- Finance 653
Countries citing papers authored by Krishna B. Athreya
This map shows the geographic impact of Krishna B. Athreya'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 Krishna B. Athreya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Krishna B. Athreya more than expected).
Fields of papers citing papers by Krishna B. Athreya
This network shows the impact of papers produced by Krishna B. Athreya. 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 Krishna B. Athreya. The network helps show where Krishna B. Athreya may publish in the future.
Co-authorship network of co-authors of Krishna B. Athreya
This figure shows the co-authorship network connecting the top 25 collaborators of Krishna B. Athreya. A scholar is included among the top collaborators of Krishna B. Athreya 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 Krishna B. Athreya. Krishna B. Athreya 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 | 20 | |
| 3 | Measure Theory and Probability Theory (Springer Texts in Statistics) | 34 |
| 4 | On the Supercritical Bellman-Harris Process with Finite Mean | 2 |
| 5 | Perfect sampling for Doeblin chains | 5 |
| 6 | KERNEL ESTIMATION FOR REAL-VALUED MARKOV CHAINS | 12 |
| 7 | 57 | |
| 8 | 10 | |
| 9 | Advances in crystallization from solutions | 5 |
| 10 | 32 | |
| 11 | 8 | |
| 12 | 1 | |
| 13 | 266 | |
| 14 | 22 | |
| 15 | 6 | |
| 16 | 6 | |
| 17 | 3 | |
| 18 | 15 | |
| 19 | 30 | |
| 20 | 38 |
About Krishna B. Athreya
Krishna B. Athreya is a scholar working on Mathematical Physics, Statistics and Probability and Finance, having authored 135 papers that have together received 3.7k indexed citations. Recurring topics across this work include Stochastic processes and statistical mechanics (73 papers), Markov Chains and Monte Carlo Methods (48 papers) and Bayesian Methods and Mixture Models (24 papers). The work is most often cited by research in Mathematical Physics (2.1k citations), Statistics and Probability (1.5k citations) and Finance (653 citations). Krishna B. Athreya has collaborated with scholars based in United States, India and South Korea. Frequent co-authors include Peter Ney, Samuel Karlin, Sastry G. Pantula, Peter Jagers, David McDonald, N. Kaplan, Jayaram Sethuraman, Hani Doss, Kevin K. Anderson and Cheng–Der Fuh. Their work appears in journals such as Science, Journal of the American Statistical Association and The Journal of Physical Chemistry.
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.