This map shows the geographic impact of Maya R. Gupta'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 Maya R. Gupta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maya R. Gupta more than expected).
This network shows the impact of papers produced by Maya R. Gupta. 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 Maya R. Gupta. The network helps show where Maya R. Gupta may publish in the future.
Co-authorship network of co-authors of Maya R. Gupta
This figure shows the co-authorship network connecting the top 25 collaborators of Maya R. Gupta.
A scholar is included among the top collaborators of Maya R. Gupta 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 Maya R. Gupta. Maya R. Gupta 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
1.
Wang, Serena & Maya R. Gupta. (2020). Deontological Ethics By Monotonicity Shape Constraints. International Conference on Artificial Intelligence and Statistics. 2043–2054.1 indexed citations
2.
Cotter, Andrew, Maya R. Gupta, & Harikrishna Narasimhan. (2019). On Making Stochastic Classifiers Deterministic. Neural Information Processing Systems. 32. 10910–10920.1 indexed citations
3.
Narasimhan, Harikrishna, Andrew Cotter, & Maya R. Gupta. (2019). Optimizing Generalized Rate Metrics with Three Players. Neural Information Processing Systems. 32. 10746–10757.4 indexed citations
4.
Cotter, Andrew, et al.. (2019). Shape Constraints for Set Functions. International Conference on Machine Learning. 1388–1396.5 indexed citations
5.
Cotter, Andrew, et al.. (2018). Constrained Interacting Submodular Groupings. International Conference on Machine Learning. 1068–1077.2 indexed citations
You, Seungil, Xin Ding, Kevin Robert Canini, Jan Pfeifer, & Maya R. Gupta. (2017). Deep Lattice Networks and Partial Monotonic Functions. neural information processing systems. 30. 2981–2989.13 indexed citations
8.
Canini, Kevin Robert, et al.. (2016). Fast and Flexible Monotonic Functions with Ensembles of Lattices. Neural Information Processing Systems. 29. 2919–2927.10 indexed citations
Goh, Gabriel, Andrew Cotter, Maya R. Gupta, & Michael P. Friedlander. (2016). Satisfying real-world goals with dataset constraints. Neural Information Processing Systems. 29. 2423–2431.9 indexed citations
11.
Gupta, Maya R., Samy Bengio, & Jason Weston. (2014). Training highly multiclass classifiers. Journal of Machine Learning Research. 15(1). 1461–1492.52 indexed citations
12.
Gupta, Maya R., et al.. (2013). Contact clustering and fusion for preprocessing multistatic active sonar data. International Conference on Information Fusion. 522–529.2 indexed citations
13.
Gupta, Maya R., et al.. (2011). Clutter rejection by clustering likelihood-based similarities. International Conference on Information Fusion. 1–6.6 indexed citations
14.
Arora, Raman, et al.. (2011). Clustering by Left-Stochastic Matrix Factorization. International Conference on Machine Learning. 761–768.18 indexed citations
15.
Frigyik, Béla A., Maya R. Gupta, & Yihua Chen. (2010). Shadow Dirichlet for Restricted Probability Modeling. Neural Information Processing Systems. 23. 613–621.4 indexed citations
Cazzanti, Luca, Maya R. Gupta, & Santosh Kumar Srivastava. (2009). Fusing similarities and Euclidean features with generative classifiers. International Conference on Information Fusion. 224–231.2 indexed citations
18.
Jamieson, Kevin, et al.. (2009). Sequential Bayesian estimation of the probability of detection for tracking. International Conference on Information Fusion. 641–648.13 indexed citations
19.
Garcia, Eric & Maya R. Gupta. (2009). Lattice Regression. Neural Information Processing Systems. 22. 594–602.6 indexed citations
20.
Srivastava, Santosh Kumar, Maya R. Gupta, & Béla A. Frigyik. (2007). Bayesian Quadratic Discriminant Analysis. Journal of Machine Learning Research. 8(46). 1277–1305.163 indexed citations
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.