Onur Teymur

13.5k total citations · 1 hit paper
7 papers, 11.3k citations indexed

About

Onur Teymur is a scholar working on Artificial Intelligence, Statistics, Probability and Uncertainty and Statistics and Probability. According to data from OpenAlex, Onur Teymur has authored 7 papers receiving a total of 11.3k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 2 papers in Statistics, Probability and Uncertainty and 2 papers in Statistics and Probability. Recurrent topics in Onur Teymur's work include Gaussian Processes and Bayesian Inference (3 papers), Neural Networks and Applications (2 papers) and Bayesian Modeling and Causal Inference (2 papers). Onur Teymur is often cited by papers focused on Gaussian Processes and Bayesian Inference (3 papers), Neural Networks and Applications (2 papers) and Bayesian Modeling and Causal Inference (2 papers). Onur Teymur collaborates with scholars based in United Kingdom, Australia and Germany. Onur Teymur's co-authors include Ben Calderhead, Jackson Gorham, Chris J. Oates, Konstantinos C. Zygalakis, Sarah Filippi, Tim Sullivan, François‐Xavier Briol and Philipp Hennig and has published in prestigious journals such as Bayesian Analysis, PubMed and arXiv (Cornell University).

In The Last Decade

Onur Teymur

7 papers receiving 11.1k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

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.

Advances in Neural Information Processing Systems 29

2016 11.3k citations Onur Teymur, Ben Calderhead et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Onur Teymur United Kingdom	3	4.7k	2.9k	875	680	642	7	11.3k
Ben Calderhead United Kingdom	12	5.2k 1.1×	3.0k 1.0×	1.1k 1.2×	693 1.0×	688 1.1×	23	12.5k
Meelis Kull Estonia	12	5.6k 1.2×	4.7k 1.6×	1.4k 1.6×	851 1.3×	748 1.2×	28	14.6k
Grégoire Montavon Germany	23	5.4k 1.1×	1.7k 0.6×	795 0.9×	599 0.9×	757 1.2×	49	10.3k
Zhen Wang China	59	3.2k 0.7×	3.4k 1.2×	605 0.7×	765 1.1×	405 0.6×	557	17.5k
James Bergstra Canada	18	4.2k 0.9×	2.1k 0.7×	518 0.6×	1.2k 1.7×	589 0.9×	25	10.1k
Wojciech Samek Germany	35	5.6k 1.2×	1.9k 0.7×	683 0.8×	659 1.0×	299 0.5×	136	11.7k
Tin Kam Ho United States	23	4.6k 1.0×	2.4k 0.8×	899 1.0×	1.1k 1.7×	529 0.8×	78	11.2k
P. M. Durai Raj Vincent India	28	4.0k 0.8×	2.7k 0.9×	677 0.8×	646 0.9×	264 0.4×	92	10.0k
Mark E. Shields United States	3	4.3k 0.9×	3.1k 1.1×	981 1.1×	659 1.0×	574 0.9×	6	10.7k
Massimiliano Pontil United Kingdom	45	4.8k 1.0×	3.7k 1.2×	1.2k 1.4×	329 0.5×	550 0.9×	139	10.7k

Countries citing papers authored by Onur Teymur

Since Specialization

Citations

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

Fields of papers citing papers by Onur Teymur

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Onur Teymur

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

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Teymur, Onur, et al.. (2022). Post-Processing of MCMC.. PubMed. 9. 529–555. 1 indexed citations

2.

Teymur, Onur, et al.. (2021). Optimal Quantisation of Probability Measures Using Maximum Mean Discrepancy. Kent Academic Repository (University of Kent). 1027–1035. 2 indexed citations

3.

Teymur, Onur & Sarah Filippi. (2020). A Bayesian nonparametric test for conditional independence. Kent Academic Repository (University of Kent). 2(2). 155–172. 1 indexed citations

4.

Teymur, Onur, et al.. (2018). Implicit Probabilistic Integrators for ODEs. Kent Academic Repository (University of Kent). 31. 7244–7253. 4 indexed citations

5.

Teymur, Onur, et al.. (2016). Advances in Neural Information Processing Systems 29. 11300 indexed citations breakdown →

6.

Teymur, Onur, Konstantinos C. Zygalakis, & Ben Calderhead. (2016). Probabilistic Linear Multistep Methods. arXiv (Cornell University). 29. 4321–4328. 4 indexed citations

7.

Briol, François‐Xavier, et al.. (2016). Contributed Discussion on Article by Chkrebtii, Campbell, Calderhead, and Girolami. Bayesian Analysis. 11(4). 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.

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