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.
Building Rome in a day
2009684 citationsSameer Agarwal, Noah Snavely et al.profile →
Building Rome in a day
2011671 citationsSameer Agarwal, Yasutaka Furukawa et al.Communications of the ACMprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Ian Simon'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 Ian Simon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ian Simon more than expected).
This network shows the impact of papers produced by Ian Simon. 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 Ian Simon. The network helps show where Ian Simon may publish in the future.
Co-authorship network of co-authors of Ian Simon
This figure shows the co-authorship network connecting the top 25 collaborators of Ian Simon.
A scholar is included among the top collaborators of Ian Simon 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 Ian Simon. Ian Simon is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Huang, Cheng-Zhi Anna, Ashish Vaswani, Jakob Uszkoreit, et al.. (2019). Music Transformer: Generating Music with Long-Term Structure. International Conference on Learning Representations.119 indexed citations
3.
Roberts, Adam P., Curtis Hawthorne, & Ian Simon. (2018). Magenta.js: A JavaScript API for Augmenting Creativity with Deep Learning.10 indexed citations
Oore, Sageev, et al.. (2017). Learning to Create Piano Performances.5 indexed citations
6.
Agarwal, Sameer, Yasutaka Furukawa, Noah Snavely, et al.. (2011). Building Rome in a day. Communications of the ACM. 54(10). 105–112.671 indexed citations breakdown →
7.
Simon, Ian. (2011). Scene Understanding Using Internet Photo Collections.1 indexed citations
Agarwal, Sameer, Noah Snavely, Ian Simon, Steven M. Seitz, & Richard Szeliski. (2009). Building Rome in a day. 72–79.684 indexed citations breakdown →
11.
Morris, Dan, Ian Simon, & Sumit Basu. (2008). Exposing parameters of a trained dynamic model for interactive music creation. National Conference on Artificial Intelligence. 784–791.18 indexed citations
Simon, Ian, Sumit Basu, David Salesin, & Maneesh Agrawala. (2005). AUDIO ANALOGIES: CREATING NEW MUSIC FROM AN EXISTING PERFORMANCE BY CONCATENATIVE SYNTHESIS. The Journal of the Abraham Lincoln Association. 2005.9 indexed citations
16.
Simon, Ian. (2004). Dilutive trade mark applications: trading on reputations or just playing games?. UCL Discovery (University College London).
17.
Pless, Robert & Ian Simon. (2002). Using Thousands of Images of an Object.. 684–687.13 indexed citations
18.
Young, R. Michael, et al.. (1989). Multiple mutually-supporting representations for procedural knowledge. 21–30.1 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.