This map shows the geographic impact of Eric Price'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 Eric Price with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Price more than expected).
This network shows the impact of papers produced by Eric Price. 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 Eric Price. The network helps show where Eric Price may publish in the future.
Co-authorship network of co-authors of Eric Price
This figure shows the co-authorship network connecting the top 25 collaborators of Eric Price.
A scholar is included among the top collaborators of Eric Price 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 Eric Price. Eric Price is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Price, Eric, et al.. (2020). On the Power of Compressed Sensing with Generative Models. International Conference on Machine Learning. 1. 5101–5109.3 indexed citations
4.
Chen, Xue & Eric Price. (2019). Active Regression via Linear-Sample Sparsification. Conference on Learning Theory. 663–695.2 indexed citations
5.
Chen, Xuebo & Eric Price. (2019). Estimating the Frequency of a Clustered Signal.. arXiv (Cornell University).1 indexed citations
Diakonikolas, Ilias, et al.. (2019). . 25(1). 1–21.3 indexed citations
8.
Bora, Ashish, Eric Price, & Alexandros G. Dimakis. (2018). AmbientGAN: Generative models from lossy measurements. International Conference on Learning Representations.43 indexed citations
9.
Bubeck, Sébastien, Eric Price, & Ilya Razenshteyn. (2018). Adversarial examples from computational constraints. International Conference on Machine Learning. 831–840.8 indexed citations
10.
Bora, Ashish, Ajil Jalal, Eric Price, & Alexandros G. Dimakis. (2017). Compressed Sensing using Generative Models. arXiv (Cornell University). 537–546.93 indexed citations
11.
Burba, George, Joseph C. von Fischer, Beniamino Gioli, et al.. (2016). Latest on Mobile Methane Measurements with Fast Open-Path Technology: Experiences, Opportunities & Perspectives. Publication Database GFZ (GFZ German Research Centre for Geosciences).1 indexed citations
Ba, Khanh Do, Piotr Indyk, Eric Price, & David P. Woodruff. (2010). Lower bounds for sparse recovery. Symposium on Discrete Algorithms. 1190–1197.60 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.