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.
Countries citing papers authored by Craig Saunders
Since
Specialization
Citations
This map shows the geographic impact of Craig Saunders'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 Craig Saunders with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Craig Saunders more than expected).
This network shows the impact of papers produced by Craig Saunders. 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 Craig Saunders. The network helps show where Craig Saunders may publish in the future.
Co-authorship network of co-authors of Craig Saunders
This figure shows the co-authorship network connecting the top 25 collaborators of Craig Saunders.
A scholar is included among the top collaborators of Craig Saunders 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 Craig Saunders. Craig Saunders 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.
Ni, Yizhao, Craig Saunders, Sándor Szedmák, & Mahesan Niranjan. (2011). Exploitation of Machine Learning Techniques in Modelling Phrase Movements for Machine Translation. Journal of Machine Learning Research. 12(1). 1–30.10 indexed citations
Saunders, Craig, et al.. (2009). Using Image Analysis and Statistical Modelling to Achieve Improved Pig Weight Predictions. 69.6 indexed citations
7.
Specia, Lucia, Marco Turchi, Zhuoran Wang, John Shawe‐Taylor, & Craig Saunders. (2009). Improving the Confidence of Machine Translation Quality Estimates. UCL Discovery (University College London).43 indexed citations
8.
Klami, Arto, Samuel Kaski, Kitsuchart Pasupa, Craig Saunders, & Teófilo de Campos. (2008). Prediction of relevance of an image from a scan pattern. ePrints Soton (University of Southampton).1 indexed citations
9.
Shawe‐Taylor, John, et al.. (2008). Basic metric learning. ePrints Soton (University of Southampton).2 indexed citations
10.
Saunders, Craig, S.R. Gunn, Marko Grobelnik, & John Shawe‐Taylor. (2006). Subspace, Latent Structure and Feature Selection techniques. UCL Discovery (University College London).43 indexed citations
11.
Saunders, Craig, Marko Grobelnik, Steve Gunn, & John Shawe‐Taylor. (2006). Subspace, Latent Structure and Feature Selection: Statistical and Optimization Perspectives Workshop, SLSFS 2005Bohinj, Slovenia, February 23-25, 2005 ... Papers (Lecture Notes in Computer Science). Springer eBooks.5 indexed citations
12.
Rousu, Juho, Craig Saunders, Sándor Szedmák, & John Shawe‐Taylor. (2006). Kernel-Based Learning of Hierarchical Multilabel Classification Models. Journal of Machine Learning Research. 7(59). 1601–1626.160 indexed citations
13.
Rousu, Juho, Craig Saunders, Sándor Szedmák, & John Shawe‐Taylor. (2005). Learning Hierarchical Multi-Category Text Classification Models. ePrints Soton (University of Southampton).1 indexed citations
14.
Saunders, Craig, et al.. (2004). Validation and application of the SCALP model. cosp. 35. 2921.1 indexed citations
15.
Rousu, Juho, Craig Saunders, Sándor Szedmák, & John Shawe‐Taylor. (2004). On Maximum Margin Hierarchical Classification. ePrints Soton (University of Southampton).1 indexed citations
16.
Saunders, Craig, et al.. (2002). Syllables and other String Kernel Extensions. UCL Discovery (University College London). 530–537.19 indexed citations
17.
Saunders, Craig, et al.. (2002). String Kernels, Fisher Kernels and Finite State Automata. ePrints Soton (University of Southampton). 15. 649–656.18 indexed citations
18.
Saunders, Craig, Alex Gammerman, & Vladimir Vovk. (1999). Transduction with Confidence and Credibility. ePrints Soton (University of Southampton). 722–726.85 indexed citations
19.
Vovk, Vladimir, Alex Gammerman, & Craig Saunders. (1999). Machine-Learning Applications of Algorithmic Randomness. ePrints Soton (University of Southampton). 444–453.83 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.