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.
Interacting multiple model methods in target tracking: a survey
This map shows the geographic impact of Amir Averbuch'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 Amir Averbuch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amir Averbuch more than expected).
This network shows the impact of papers produced by Amir Averbuch. 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 Amir Averbuch. The network helps show where Amir Averbuch may publish in the future.
Co-authorship network of co-authors of Amir Averbuch
This figure shows the co-authorship network connecting the top 25 collaborators of Amir Averbuch.
A scholar is included among the top collaborators of Amir Averbuch 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 Amir Averbuch. Amir Averbuch is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Averbuch, Amir, et al.. (2017). Uncovering Unknown Unknowns in Financial Services Big Data by Unsupervised Methodologies: Present and Future trends. Knowledge Discovery and Data Mining. 8–19.3 indexed citations
6.
Averbuch, Amir, et al.. (2016). Randomized LU decomposition. Applied and Computational Harmonic Analysis. 44(2). 246–272.31 indexed citations
7.
Averbuch, Amir, et al.. (2013). LgDb 2.0: Using Lguest for kernel profiling, code coverage and simulation. International Symposium on Performance Evaluation of Computer and Telecommunication Systems. 78–85.6 indexed citations
Turkka, Jussi, et al.. (2011). Anomaly Detection Framework for Tracing Problems in Radio Networks. 317–321.4 indexed citations
10.
Averbuch, Amir, et al.. (2011). Using virtualization for online kernel profiling, code coverage and instrumentation. International Symposium on Performance Evaluation of Computer and Telecommunication Systems. 104–110.4 indexed citations
11.
Rabin, Neta & Amir Averbuch. (2010). Detection of Anomaly Trends in Dynamically Evolving Systems. National Conference on Artificial Intelligence.8 indexed citations
12.
Averbuch, Amir, et al.. (2010). Hierarchical Clustering Via Localized Diffusion Folders. National Conference on Artificial Intelligence.3 indexed citations
Averbuch, Amir, et al.. (1991). Asynchronous and corrected-asynchronous numerical solutions of parabolic PDES on MIMD multiprocessors.1 indexed citations
20.
Gohberg, Israel, et al.. (1991). Timing Analysis of a Parallel Algorithm for Toeplitz Matrices on a MIMD Parallel Machine.. Proceedings of the International Conference on Parallel Processing. 312–313.3 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.