Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Optimal-Transport Analysis of Single-Cell Gene Expression Identifies Developmental Trajectories in Reprogramming
2019409 citationsGeoffrey Schiebinger, Jian Shu et al.Cellprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Philippe Rigollet
Since
Specialization
Citations
This map shows the geographic impact of Philippe Rigollet'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 Philippe Rigollet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philippe Rigollet more than expected).
Fields of papers citing papers by Philippe Rigollet
This network shows the impact of papers produced by Philippe Rigollet. 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 Philippe Rigollet. The network helps show where Philippe Rigollet may publish in the future.
Co-authorship network of co-authors of Philippe Rigollet
This figure shows the co-authorship network connecting the top 25 collaborators of Philippe Rigollet.
A scholar is included among the top collaborators of Philippe Rigollet 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 Philippe Rigollet. Philippe Rigollet is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Meka, Raghu, et al.. (2020). Balancing Gaussian vectors in high dimension. Conference on Learning Theory. 3455–3486.1 indexed citations
7.
Hütter, Jan-Christian & Philippe Rigollet. (2019). Minimax rates of estimation for smooth optimal transport maps. arXiv (Cornell University).5 indexed citations
8.
Forrow, Aden, et al.. (2019). Statistical optimal transport via factored couplings. Oxford University Research Archive (ORA) (University of Oxford).3 indexed citations
9.
Schiebinger, Geoffrey, Jian Shu, Marcin Tabaka, et al.. (2019). Optimal-Transport Analysis of Single-Cell Gene Expression Identifies Developmental Trajectories in Reprogramming. Cell. 176(4). 928–943.e22.409 indexed citations breakdown →
10.
Altschuler, Jason M., Jonathan Weed, & Philippe Rigollet. (2017). Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration. DSpace@MIT (Massachusetts Institute of Technology). 30. 1964–1974.28 indexed citations
11.
Weed, Jonathan, Vianney Perchet, & Philippe Rigollet. (2016). Online learning in repeated auctions. Journal of Machine Learning Research. 49. 1562–1583.7 indexed citations
12.
Rigollet, Philippe, et al.. (2016). Optimal rates for total variation denoising. Conference on Learning Theory. 1115–1146.8 indexed citations
13.
Berthet, Quentin & Philippe Rigollet. (2013). Complexity Theoretic Lower Bounds for Sparse Principal Component Detection. Conference on Learning Theory. 1046–1066.73 indexed citations
14.
Bubeck, Sébastien, Vianney Perchet, & Philippe Rigollet. (2013). Bounded regret in stochastic multi-armed bandits. Conference on Learning Theory. 122–134.18 indexed citations
15.
Rigollet, Philippe & Xin Tong. (2011). Neyman-Pearson Classification, Convexity and Stochastic Constraints. Journal of Machine Learning Research. 12(86). 2831–2855.17 indexed citations
16.
Rigollet, Philippe & Xin Tong. (2011). Neyman-Pearson classification under a strict constraint. The HKU Scholars Hub (University of Hong Kong). 595–614.2 indexed citations
17.
Rigollet, Philippe & Assaf Zeevi. (2010). Nonparametric Bandits with Covariates. Conference on Learning Theory. 54–66.11 indexed citations
18.
Rigollet, Philippe. (2009). Maximum likelihood aggregation and misspecified generalized linear models. arXiv (Cornell University).1 indexed citations
Rigollet, Philippe. (2007). Generalization error bounds in semi-supervised classification under the cluster assumption. ArXiv.org.1 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.