Countries citing papers authored by Nilesh Tripuraneni
Since
Specialization
Citations
This map shows the geographic impact of Nilesh Tripuraneni'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 Nilesh Tripuraneni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nilesh Tripuraneni more than expected).
Fields of papers citing papers by Nilesh Tripuraneni
This network shows the impact of papers produced by Nilesh Tripuraneni. 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 Nilesh Tripuraneni. The network helps show where Nilesh Tripuraneni may publish in the future.
Co-authorship network of co-authors of Nilesh Tripuraneni
This figure shows the co-authorship network connecting the top 25 collaborators of Nilesh Tripuraneni.
A scholar is included among the top collaborators of Nilesh Tripuraneni 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 Nilesh Tripuraneni. Nilesh Tripuraneni is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Tripuraneni, Nilesh, Ben Adlam, & Jeffrey Pennington. (2021). Overparameterization Improves Robustness to Covariate Shift in High Dimensions. Neural Information Processing Systems. 34.8 indexed citations
3.
Liu, Runjing, Jeffrey Regier, Nilesh Tripuraneni, Michael I. Jordan, & Jon McAuliffe. (2019). Rao-Blackwellized Stochastic Gradients for Discrete Distributions. International Conference on Machine Learning. 4023–4031.3 indexed citations
4.
Tripuraneni, Nilesh, Mitchell Stern, Chi Jin, Jeffrey Regier, & Michael I. Jordan. (2018). Stochastic Cubic Regularization for Fast Nonconvex Optimization. Neural Information Processing Systems. 31. 2899–2908.20 indexed citations
5.
Tripuraneni, Nilesh, Nicolas Flammarion, Francis Bach, & Michael I. Jordan. (2018). Averaging Stochastic Gradient Descent on Riemannian Manifolds. HAL (Le Centre pour la Communication Scientifique Directe).1 indexed citations
6.
Tripuraneni, Nilesh, Mark Rowland, Zoubin Ghahramani, & Richard E. Turner. (2017). Magnetic hamiltonian Monte Carlo. Cambridge University Engineering Department Publications Database. 3453–3461.13 indexed citations
7.
Dexter, Joseph P., Nilesh Tripuraneni, Tathagata Dasgupta, et al.. (2017). Quantitative criticism of literary relationships. Proceedings of the National Academy of Sciences. 114(16). E3195–E3204.11 indexed citations
8.
Balog, Matej, Nilesh Tripuraneni, Zoubin Ghahramani, & Adrian Weller. (2017). Lost Relatives of the Gumbel Trick. Apollo (University of Cambridge). 371–379.4 indexed citations
9.
Tripuraneni, Nilesh, Shixiang Gu, Hong Ge, & Zoubin Ghahramani. (2015). Particle Gibbs for Infinite Hidden Markov Models. Cambridge University Engineering Department Publications Database. 28. 2395–2403.9 indexed citations
10.
Bauer, Steven, Max Kleiman‐Weiner, Daniel A. Roberts, et al.. (2013). Evaluating Stream Filtering for Entity Profile Updates for TREC 2013.. Text REtrieval Conference.12 indexed citations
11.
Bauer, Steven, Max Kleiman‐Weiner, Daniel A. Roberts, et al.. (2013). Evaluating Stream Filtering for Entity Profile Updates for TREC 2013 (KBA Track Overview).3 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.