This map shows the geographic impact of Karl Stratos'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 Karl Stratos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karl Stratos more than expected).
This network shows the impact of papers produced by Karl Stratos. 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 Karl Stratos. The network helps show where Karl Stratos may publish in the future.
Co-authorship network of co-authors of Karl Stratos
This figure shows the co-authorship network connecting the top 25 collaborators of Karl Stratos.
A scholar is included among the top collaborators of Karl Stratos 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 Karl Stratos. Karl Stratos is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kim, Young‐Bum, Karl Stratos, & Ruhi Sarikaya. (2016). Domainless Adaptation by Constrained Decoding on a Schema Lattice.. International Conference on Computational Linguistics. 2051–2060.9 indexed citations
10.
Kim, Young‐Bum, Karl Stratos, & Ruhi Sarikaya. (2016). Frustratingly Easy Neural Domain Adaptation. International Conference on Computational Linguistics. 387–396.45 indexed citations
Cohen, Shay B., Karl Stratos, Michael Collins, Dean P. Foster, & Lyle Ungar. (2014). Spectral learning of latent-variable PCFGs: algorithms and sample complexity. Journal of Machine Learning Research. 15(1). 2399–2449.13 indexed citations
14.
Stratos, Karl, et al.. (2014). A spectral algorithm for learning class-based n -gram models of natural language. Uncertainty in Artificial Intelligence. 762–771.18 indexed citations
15.
Stratos, Karl, Alexander M. Rush, Shay B. Cohen, & Michael Collins. (2013). Spectral Learning of Refinement HMMs. Edinburgh Research Explorer (University of Edinburgh). 56–64.8 indexed citations
16.
Cohen, Shay B., Karl Stratos, Michael Collins, Dean P. Foster, & Lyle Ungar. (2012). Spectral Learning of Latent-Variable PCFGs. Edinburgh Research Explorer (University of Edinburgh). 1. 223–231.11 indexed citations
Dodge, Jesse, Amit Goyal, Xufeng Han, et al.. (2012). Detecting Visual Text. 762–772.29 indexed citations
20.
Schubert, Lenhart K., et al.. (2011). Towards Adequate Knowledge and Natural Inference. UR Research (University of Rochester). 288–296.1 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.