Siddharth Swaroop

461 total citations
13 papers, 118 citations indexed

About

Siddharth Swaroop is a scholar working on Artificial Intelligence, Endocrinology and Experimental and Cognitive Psychology. According to data from OpenAlex, Siddharth Swaroop has authored 13 papers receiving a total of 118 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 3 papers in Endocrinology and 2 papers in Experimental and Cognitive Psychology. Recurrent topics in Siddharth Swaroop's work include Vibrio bacteria research studies (3 papers), Gaussian Processes and Bayesian Inference (3 papers) and Explainable Artificial Intelligence (XAI) (2 papers). Siddharth Swaroop is often cited by papers focused on Vibrio bacteria research studies (3 papers), Gaussian Processes and Bayesian Inference (3 papers) and Explainable Artificial Intelligence (XAI) (2 papers). Siddharth Swaroop collaborates with scholars based in United States, United Kingdom and Switzerland. Siddharth Swaroop's co-authors include K Uemura, Finale Doshi‐Velez, Richard E. Turner, Zana Buçinca, Krzysztof Z. Gajos, Mohammad Emtiyaz Khan, Rio Yokota, Kazuki Osawa, Pingbo Pan and Andrew Y. K. Foong and has published in prestigious journals such as arXiv (Cornell University), PubMed and Neural Information Processing Systems.

In The Last Decade

Siddharth Swaroop

10 papers receiving 100 citations

Peers

Siddharth Swaroop
Comparison fields: 5 of 52
  • Artificial Intelligence 38
  • Plant Science 31
  • Insect Science 21
  • Public Health, Environmental and Occupational Health 16
  • Molecular Biology 14
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Citations per field, relative to Siddharth Swaroop
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Citations per year, relative to Siddharth Swaroop
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Countries citing papers authored by Siddharth Swaroop

Since Specialization
Citations

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

Fields of papers citing papers by Siddharth Swaroop

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Siddharth Swaroop

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

All Works

13 of 13 papers shown
# Work Indexed citations
1 5
2 2
3 0
4 15
5 1
6
Collapsed Variational Bounds for Bayesian Neural Networks
2
7
Efficient Low Rank Gaussian Variational Inference for Neural Networks
5
8
Continual Deep Learning by Functional Regularisation of Memorable Past
6
9
Practical Deep Learning with Bayesian Principles
15
10
Statistical methods in malaria eradication.
50
11
Cholera studies. 2. World incidence.
6
12
Endemicity of cholera in India.
10
13
Endemicity of cholera in relation to fairs and festivals in India.
1

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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