This map shows the geographic impact of Michael Revow'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 Michael Revow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Revow more than expected).
This network shows the impact of papers produced by Michael Revow. 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 Michael Revow. The network helps show where Michael Revow may publish in the future.
Co-authorship network of co-authors of Michael Revow
This figure shows the co-authorship network connecting the top 25 collaborators of Michael Revow.
A scholar is included among the top collaborators of Michael Revow 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 Michael Revow. Michael Revow is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Williams, Christopher K. I., Michael Revow, & Geoffrey E. Hinton. (1997). Instantiating Deformable Models with a Neural Net. Computer Vision and Image Understanding. 68(1). 120–126.7 indexed citations
5.
Revow, Michael, Christopher K. I. Williams, & Geoffrey E. Hinton. (1996). Using generative models for handwritten digit recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence. 18(6). 592–606.110 indexed citations
6.
Hinton, Geoffrey E. & Michael Revow. (1995). Using Pairs of Data-Points to Define Splits for Decision Trees. Neural Information Processing Systems. 8. 507–513.8 indexed citations
7.
Hinton, Geoffrey E., Michael Revow, & Peter Dayan. (1994). Recognizing Handwritten Digits Using Mixtures of Linear Models. UCL Discovery (University College London). 1015–1022.64 indexed citations
8.
Williams, Christopher K. I., Michael Revow, & Geoffrey E. Hinton. (1994). Using a neural net to instantiate a deformable model. Neural Information Processing Systems. 7. 965–972.5 indexed citations
9.
Williams, Christopher K. I., Michael Revow, & Geoffrey E. Hinton. (1994). Hand-printed digit recognition using deformable models. Edinburgh Research Explorer. 127–147.3 indexed citations
10.
Hinton, Geoffrey E., Christopher K. I. Williams, & Michael Revow. (1992). Combining two methods of recognizing hand-printed digits. 2. 53–60.4 indexed citations
11.
Hinton, Geoffrey E., Christopher K. I. Williams, & Michael Revow. (1991). Adaptive Elastic Models for Hand-Printed Character Recognition. Edinburgh Research Explorer. 4. 512–519.54 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.