Rajesh Ranganath

7.0k total citations · 1 hit paper
60 papers, 2.9k citations indexed

About

Rajesh Ranganath is a scholar working on Artificial Intelligence, Statistics and Probability and Computer Vision and Pattern Recognition. According to data from OpenAlex, Rajesh Ranganath has authored 60 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Artificial Intelligence, 15 papers in Statistics and Probability and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Rajesh Ranganath's work include Statistical Methods and Inference (11 papers), Machine Learning in Healthcare (9 papers) and Gaussian Processes and Bayesian Inference (9 papers). Rajesh Ranganath is often cited by papers focused on Statistical Methods and Inference (11 papers), Machine Learning in Healthcare (9 papers) and Gaussian Processes and Bayesian Inference (9 papers). Rajesh Ranganath collaborates with scholars based in United States, Netherlands and Canada. Rajesh Ranganath's co-authors include Roger Grosse, Honglak Lee, Andrew Y. Ng, David M. Blei, Marzyeh Ghassemi, Daniel A. McFarland, Dan Jurafsky, Luca Foschini, Andrew L. Beam and Peter Schulam and has published in prestigious journals such as Nature Medicine, SHILAP Revista de lepidopterología and Journal of the American Statistical Association.

In The Last Decade

Rajesh Ranganath

59 papers receiving 2.7k citations

Hit Papers

Convolutional deep belief networks for scalable unsupervi... 2009 2026 2014 2020 2009 500 1000 1.5k

Peers

Rajesh Ranganath
Comparison fields: 5 of 175
  • Artificial Intelligence 1.3k
  • Computer Vision and Pattern Recognition 1.1k
  • Signal Processing 260
  • Cognitive Neuroscience 202
  • Radiology, Nuclear Medicine and Imaging 177
Replace Sebastian Lapuschkin with:
Sebastian Lapuschkin Germany
Chaitanya Ahuja United States
Abir Hussain United Kingdom
Farhad Pourpanah China
Atsuto Maki Japan
Simone Scardapane Italy
Yang Cong China
Antonia Creswell United Kingdom
Wei Peng United States
Eyad Elyan United Kingdom
Sebastian Lapuschkin Germany View profile →
Citations per field, relative to Rajesh Ranganath
Rajesh Ranganath · 1×
Citations per year, relative to Rajesh Ranganath
Rajesh Ranganath · 1×

Countries citing papers authored by Rajesh Ranganath

Since Specialization
Citations

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

Fields of papers citing papers by Rajesh Ranganath

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rajesh Ranganath

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 5
2 0
3 4
4 3
5 1
6 2
7
General Control Functions for Causal Effect Estimation from IVs
2
8 90
9
Reproducibility in Machine Learning for Health
3
10
Noisin: Unbiased Regularization for Recurrent Neural Networks
1
11
Max-margin learning with the Bayes factor
1
12
Variational Sequential Monte Carlo
23
13
Deep Survival Analysis: Nonparametrics and Missingness.
6
14 21
15
Deep and Hierarchical Implicit Models.
20
16
Deep Exponential Families
33
17
The survival filter: joint survival analysis with a latent time series
12
18
The population posterior and Bayesian modeling on streams
14
19
Deterministic Annealing for Stochastic Variational Inference.
1
20
Bayesian Nonparametric Poisson Factorization for Recommendation Systems
42

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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