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.
Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance
20101.2k citationsNguyễn Xuân Vinh, Julien Epps et al.Journal of Machine Learning Researchprofile →
The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing
20151.1k citationsFlorian Eyben, Björn W. Schuller et al.IEEE Transactions on Affective Computingprofile →
A review of depression and suicide risk assessment using speech analysis
2015606 citationsNicholas Cummins, Jarek Krajewski et al.Speech Communicationprofile →
Information theoretic measures for clusterings comparison
2009535 citationsNguyễn Xuân Vinh, Julien Epps et al.profile →
Mamba in Speech: Towards an Alternative to Self-Attention
202512 citationsXiangyu Zhang, Qiquan Zhang et al.IEEE Transactions on Audio Speech and Language Processingprofile →
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 Julien Epps'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 Julien Epps with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julien Epps more than expected).
This network shows the impact of papers produced by Julien Epps. 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 Julien Epps. The network helps show where Julien Epps may publish in the future.
Co-authorship network of co-authors of Julien Epps
This figure shows the co-authorship network connecting the top 25 collaborators of Julien Epps.
A scholar is included among the top collaborators of Julien Epps 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 Julien Epps. Julien Epps is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Zhang, Xiangyu, Qiquan Zhang, Hexin Liu, et al.. (2025). Mamba in Speech: Towards an Alternative to Self-Attention. IEEE Transactions on Audio Speech and Language Processing. 33. 1933–1948.12 indexed citations breakdown →
Sethu, Vidhyasaharan, et al.. (2017). Gaussian Process Regression for Continuous Emotion Recognition with Global Temporal Invariance. International Joint Conference on Artificial Intelligence. 34–44.7 indexed citations
11.
Schuller, Björn W., Stefan Steidl, Anton Batliner, et al.. (2014). The INTERSPEECH 2014 Computational Paralinguistics Challenge: Cognitive & Physical Load, Multitasking. Conference of the International Speech Communication Association.2 indexed citations
Ambikairajah, Eliathamby, Julien Epps, Ming Sheng, & Branko G. Celler. (2007). Tablet PC and Electronic Whiteboard Use in Signal Processing Education. IEEE Signal Processing Magazine. 24(1). 130–133.7 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.