Ravin Kumar

1.5k citations
4 papers · 637 indexed · 2 hit papers · h-index 4
Topics
Computational Physics and Python Applications (3 papers)Gaussian Processes and Bayesian Inference (2 papers)Time Series Analysis and Forecasting (2 papers)
Journals
Journal of Statistical SoftwarePeerJ Computer ScienceThe Journal of Open Source Software

In The Last Decade

Ravin Kumar

4 papers receiving 602 citations

Hit Papers

ArviZ a unified library for exploratory analysis of Bayes...201920262021202320192023100200300

Peers

Ravin Kumar
Comparison fields: 5 of 151
  • Astronomy and Astrophysics 149
  • Artificial Intelligence 76
  • Cognitive Neuroscience 69
  • Molecular Biology 65
  • Instrumentation 45
Replace Osvaldo A. Martin with:
Osvaldo A. Martin Argentina
Ari Hartikainen Finland
Oriol Abril Argentina
Michael Osthege Germany
Robert Zinkov United States
Teresa Henriques Portugal
Virgile Andreani United States
G. Cowan United Kingdom
William T. Scott United States
Phil Gregory Australia
Ravin Kumar relative to Osvaldo A. Martin Argentina Osvaldo A. Martin's profile →
Citations per field
00.5×1.5×
Osvaldo A. Martin · 1×
Citations per year

Countries citing papers authored by Ravin Kumar

Since Specialization
Citations

This map shows the geographic impact of Ravin Kumar'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 Ravin Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ravin Kumar more than expected).

Fields of papers citing papers by Ravin Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ravin Kumar. 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 Ravin Kumar. The network helps show where Ravin Kumar may publish in the future.

Co-authorship network of co-authors of Ravin Kumar

This figure shows the co-authorship network connecting the top 25 collaborators of Ravin Kumar. A scholar is included among the top collaborators of Ravin Kumar 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 Ravin Kumar. Ravin Kumar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

4 of 4 papers shown
#WorkIndexed citations
1
PyMC: a modern, and comprehensive probabilistic programming framework in Pythonbreakdown →
244
2 41
3 22
4
ArviZ a unified library for exploratory analysis of Bayesian models in Pythonbreakdown →
330

About Ravin Kumar

Ravin Kumar is a scholar working on Signal Processing, Artificial Intelligence and Statistics and Probability, having authored 4 papers that have together received 637 indexed citations. Recurring topics across this work include Computational Physics and Python Applications (3 papers), Gaussian Processes and Bayesian Inference (2 papers) and Time Series Analysis and Forecasting (2 papers). The work is most often cited by research in Instrumentation (45 citations), Astronomy and Astrophysics (149 citations) and General Decision Sciences (15 citations). Ravin Kumar has collaborated with scholars based in Argentina, Finland and United States. Frequent co-authors include Osvaldo A. Martin, Ari Hartikainen, Christian C. Luhmann, Michael Osthege, Thomas V. Wiecki, Virgile Andreani, Robert Zinkov, Junpeng Lao, Oriol Abril and Christopher Fonnesbeck. Their work appears in journals such as Journal of Statistical Software, PeerJ Computer Science and The Journal of Open Source Software.

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.

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