Jeremy York

10.8k total citations · 3 hit papers
6 papers, 7.2k citations indexed

About

Jeremy York is a scholar working on Statistics and Probability, Artificial Intelligence and Information Systems. According to data from OpenAlex, Jeremy York has authored 6 papers receiving a total of 7.2k indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Statistics and Probability, 2 papers in Artificial Intelligence and 1 paper in Information Systems. Recurrent topics in Jeremy York's work include Statistical Methods and Bayesian Inference (2 papers), Statistical Methods and Inference (2 papers) and Bayesian Modeling and Causal Inference (2 papers). Jeremy York is often cited by papers focused on Statistical Methods and Bayesian Inference (2 papers), Statistical Methods and Inference (2 papers) and Bayesian Modeling and Causal Inference (2 papers). Jeremy York collaborates with scholars based in United States, France and Norway. Jeremy York's co-authors include Brent Smith, Greg Linden, Julian Besag, David Madigan, Denis Allard, Rolv T. Lie and Ivar Heuch and has published in prestigious journals such as Artificial Intelligence, Journal of the Royal Statistical Society Series C (Applied Statistics) and International Statistical Review.

In The Last Decade

Jeremy York

6 papers receiving 6.7k citations

Hit Papers

align trajectories

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.

Amazon.com recommendations: item-to-item collaborative filtering

2003 3.4k citations Greg Linden, Brent Smith et al. IEEE Internet Computing profile →
Bayesian image restoration, with two applications in spatial statistics

1991 3.0k citations Julian Besag, Jeremy York et al. Annals of the Institute of Statistical Mathematics profile →
Bayesian Graphical Models for Discrete Data

1995 683 citations David Madigan, Jeremy York et al. International Statistical Review profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jeremy York United States	5	2.8k	1.8k	1.2k	933	903	6	7.2k
Stephen E. Fienberg United States	39	838 0.3×	2.6k 1.4×	360 0.3×	270 0.3×	991 1.1×	111	6.5k
Anirban Dasgupta United States	29	782 0.3×	2.0k 1.1×	544 0.5×	781 0.8×	996 1.1×	108	7.5k
Shu‐Kay Ng Australia	33	910 0.3×	2.2k 1.2×	342 0.3×	599 0.6×	349 0.4×	179	7.7k
Chris Volinsky United States	24	7.5k 2.7×	5.6k 3.1×	532 0.5×	2.7k 2.9×	974 1.1×	34	14.1k
Xiao‐Jun Zeng United Kingdom	37	790 0.3×	3.7k 2.1×	981 0.8×	416 0.4×	706 0.8×	240	10.0k
Wei‐Yin Loh United States	36	985 0.4×	2.1k 1.2×	263 0.2×	375 0.4×	1.2k 1.3×	102	7.2k
David Spiegelhalter United Kingdom	33	239 0.1×	1.7k 0.9×	843 0.7×	265 0.3×	791 0.9×	77	7.5k
Alan F. Karr United States	38	1.3k 0.5×	1.5k 0.9×	259 0.2×	142 0.2×	867 1.0×	147	6.0k
Mark S. Handcock United States	44	311 0.1×	1.4k 0.8×	1.2k 1.0×	230 0.2×	1.0k 1.1×	140	11.6k
Kevin Lang United States	45	657 0.2×	3.4k 1.9×	2.6k 2.2×	1.1k 1.2×	255 0.3×	132	11.2k

Countries citing papers authored by Jeremy York

Since Specialization

Citations

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

Fields of papers citing papers by Jeremy York

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeremy York

This figure shows the co-authorship network connecting the top 25 collaborators of Jeremy York. A scholar is included among the top collaborators of Jeremy York 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 Jeremy York. Jeremy York 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:

6 of 6 papers shown

1.

Linden, Greg, Brent Smith, & Jeremy York. (2003). Amazon.com recommendations: item-to-item collaborative filtering. IEEE Internet Computing. 7(1). 76–80. 3434 indexed citations breakdown →

2.

Madigan, David, Jeremy York, & Denis Allard. (1995). Bayesian Graphical Models for Discrete Data. International Statistical Review. 63(2). 215–215. 683 indexed citations breakdown →

3.

York, Jeremy, David Madigan, Ivar Heuch, & Rolv T. Lie. (1995). Birth Defects Registered by Double Sampling: A Bayesian Approach Incorporating Covariates and Model Uncertainty. Journal of the Royal Statistical Society Series C (Applied Statistics). 44(2). 227–227. 36 indexed citations

4.

York, Jeremy. (1992). Use of the Gibbs sampler in expert systems. Artificial Intelligence. 56(1). 115–130. 20 indexed citations

5.

York, Jeremy. (1992). Use of the Gibbs sampler in expert systems. Artificial Intelligence. 56(2-3). 397–398. 1 indexed citations

6.

Besag, Julian, et al.. (1991). Bayesian image restoration, with two applications in spatial statistics. Annals of the Institute of Statistical Mathematics. 43(1). 1–20. 2993 indexed citations breakdown →

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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