Purnamrita Sarkar
- Artificial Intelligence top 2%
- Statistical and Nonlinear Physics top 1%
- Statistics and Probability top 2%
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Andrew MooreMichael I. JordanAriel KleinerAmeet TalwalkarDeepayan ChakrabartiTim KraskaMichael J. FranklinBeth Trushkowsky
- Topics
- Complex Network Analysis Techniques (16 papers)Bayesian Methods and Mixture Models (7 papers)Statistical Methods and Inference (6 papers)
- Partner nations
- United StatesAustraliaUnited Kingdom
In The Last Decade
Purnamrita Sarkar
32 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 119
- Artificial Intelligence 536
- Statistical and Nonlinear Physics 496
- Statistics and Probability 158
- Computer Networks and Communications 140
- Computer Vision and Pattern Recognition 134
Countries citing papers authored by Purnamrita Sarkar
This map shows the geographic impact of Purnamrita Sarkar'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 Purnamrita Sarkar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Purnamrita Sarkar more than expected).
Fields of papers citing papers by Purnamrita Sarkar
This network shows the impact of papers produced by Purnamrita Sarkar. 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 Purnamrita Sarkar. The network helps show where Purnamrita Sarkar may publish in the future.
Co-authorship network of co-authors of Purnamrita Sarkar
This figure shows the co-authorship network connecting the top 25 collaborators of Purnamrita Sarkar. A scholar is included among the top collaborators of Purnamrita Sarkar 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 Purnamrita Sarkar. Purnamrita Sarkar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | When random initializations help: a study of variational inference for community detection | 1 |
| 3 | Consistent Nonparametric Methods for Network Assisted Covariate Estimation | 1 |
| 4 | On hyperparameter tuning in general clustering problemsm | 0 |
| 5 | Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues | 4 |
| 6 | Overlapping Clustering Models, and One (class) SVM to Bind Them All | 5 |
| 7 | Exact Recovery of Number of Blocks in Blockmodels | 2 |
| 8 | Statistical Convergence Analysis of Gradient EM on General Gaussian Mixture Models | 0 |
| 9 | Convergence of Gradient EM on Multi-component Mixture of Gaussians | 12 |
| 10 | On Robustness of Kernel Clustering | 5 |
| 11 | The consistency of common neighbors for link prediction in stochastic blockmodels | 4 |
| 12 | 218 | |
| 13 | Application of Chemometric methods for assessment of heavy metal pollution and source apportionment in Riparian zone soil of Ulhas River estuary, India | 13 |
| 14 | Non-parametric Link Prediction | 1 |
| 15 | 26 | |
| 16 | 67 | |
| 17 | 5 | |
| 18 | A Latent Space Approach to Dynamic Embedding of Co-occurrence Data | 41 |
| 19 | A tractable approach to finding closest truncated-commute-time neighbors in large graphs | 50 |
| 20 | Dynamic Social Network Analysis using Latent Space Models | 5 |
About Purnamrita Sarkar
Purnamrita Sarkar is a scholar working on Statistical and Nonlinear Physics, Statistics and Probability and Artificial Intelligence, having authored 35 papers that have together received 1.1k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (16 papers), Bayesian Methods and Mixture Models (7 papers) and Statistical Methods and Inference (6 papers). The work is most often cited by research in Statistical and Nonlinear Physics (496 citations), Computational Mathematics (14 citations) and Statistics and Probability (158 citations). Purnamrita Sarkar has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Andrew Moore, Michael I. Jordan, Ariel Kleiner, Ameet Talwalkar, Deepayan Chakrabarti, Tim Kraska, Michael J. Franklin, Beth Trushkowsky, Andrew W. Moore and Amit Prakash. Their work appears in journals such as Journal of the American Statistical Association, Communications of the ACM and Biometrika.
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.