Onureena Banerjee
- Statistics and Probability top 1%
- Artificial Intelligence top 5%
- Computational Mechanics top 5%
- Molecular Biology
- Signal Processing top 10%
- Co-authors
- Alexandre d’AspremontLaurent El GhaouiGeorges NatsoulisVivian ViallonÉric JouglaJoël CosteGrégoire Rey
- Topics
- Statistical Methods and Inference (5 papers)Bayesian Modeling and Causal Inference (2 papers)Machine Learning and Algorithms (2 papers)
- Journals
- Journal of Machine Learning ResearchSIAM Journal on Matrix Analysis and ApplicationsBiometrical Journal
- Partner nations
- United StatesFrance
In The Last Decade
Onureena Banerjee
5 papers receiving 969 citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Statistics and Probability 472
- Artificial Intelligence 423
- Computational Mechanics 239
- Molecular Biology 222
- Signal Processing 93
Countries citing papers authored by Onureena Banerjee
This map shows the geographic impact of Onureena Banerjee'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 Onureena Banerjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Onureena Banerjee more than expected).
Fields of papers citing papers by Onureena Banerjee
This network shows the impact of papers produced by Onureena Banerjee. 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 Onureena Banerjee. The network helps show where Onureena Banerjee may publish in the future.
Co-authorship network of co-authors of Onureena Banerjee
This figure shows the co-authorship network connecting the top 25 collaborators of Onureena Banerjee. A scholar is included among the top collaborators of Onureena Banerjee 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 Onureena Banerjee. Onureena Banerjee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Databreakdown → | 732 |
| 3 | 204 | |
| 4 | Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data | 1 |
| 5 | 94 |
About Onureena Banerjee
Onureena Banerjee is a scholar working on Statistics and Probability, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 5 papers that have together received 1.0k indexed citations. Recurring topics across this work include Statistical Methods and Inference (5 papers), Bayesian Modeling and Causal Inference (2 papers) and Machine Learning and Algorithms (2 papers). The work is most often cited by research in Statistics and Probability (472 citations), Artificial Intelligence (423 citations) and Computational Mathematics (7 citations). Onureena Banerjee has collaborated with scholars based in United States and France. Frequent co-authors include Alexandre d’Aspremont, Laurent El Ghaoui, Georges Natsoulis, Vivian Viallon, Éric Jougla, Joël Coste and Grégoire Rey. Their work appears in journals such as Journal of Machine Learning Research, SIAM Journal on Matrix Analysis and Applications and Biometrical Journal.
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.