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.
Adversarial Discriminative Domain Adaptation
20173.0k citationsEric Tzeng, Judy Hoffman et al.profile →
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
20132.1k citationsJeff Donahue, Yangqing Jia et al.arXiv (Cornell University)profile →
Simultaneous Deep Transfer Across Domains and Tasks
2015690 citationsEric Tzeng, Judy Hoffman et al.profile →
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 Eric Tzeng'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 Tzeng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Tzeng more than expected).
This network shows the impact of papers produced by Eric Tzeng. 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 Tzeng. The network helps show where Eric Tzeng may publish in the future.
Co-authorship network of co-authors of Eric Tzeng
This figure shows the co-authorship network connecting the top 25 collaborators of Eric Tzeng.
A scholar is included among the top collaborators of Eric Tzeng 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 Tzeng. Eric Tzeng is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Azadi, Samaneh, Michael Tschannen, Eric Tzeng, et al.. (2021). Unconditional Synthesis of Complex Scenes Using a Semantic Bottleneck.1 indexed citations
Hoffman, Judy, Deepak Pathak, Eric Tzeng, et al.. (2016). Large scale visual recognition through adaptation using joint representation and multiple instance learning. 17(1). 4954–4984.8 indexed citations
10.
Tzeng, Eric, Judy Hoffman, Trevor Darrell, & Kate Saenko. (2015). Simultaneous Deep Transfer Across Domains and Tasks. 4068–4076.690 indexed citations breakdown →
Hoffman, Judy, Sergio Guadarrama, Eric Tzeng, et al.. (2014). From Large-Scale Object Classifiers to Large-Scale Object Detectors: An Adaptation Approach.2 indexed citations
Hoffman, Judy, Eric Tzeng, Jeff Donahue, et al.. (2013). One-Shot Adaptation of Supervised Deep Convolutional Models. arXiv (Cornell University).10 indexed citations
17.
Donahue, Jeff, Yangqing Jia, Oriol Vinyals, et al.. (2013). DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition. arXiv (Cornell University). 647–655.2085 indexed citations breakdown →
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.