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.
Countries citing papers authored by A. Sherstinsky
Since Specialization
Citations
This map shows the geographic impact of A. Sherstinsky'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 A. Sherstinsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. Sherstinsky more than expected).
This network shows the impact of papers produced by A. Sherstinsky. 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 A. Sherstinsky. The network helps show where A. Sherstinsky may publish in the future.
Co-authorship network
The 4 scholars most cited alongside A. Sherstinsky, linked wherever they have
co-authored with each other. Click a name or a connecting line to browse the papers they
share.
Border = papers with A. SherstinskyLine = papers co-authored togetherA. Sherstinsky links everyone, so they are left out of the graph.
All Works
10 of 10 papers shown
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Work
1
Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) networkbreakdown →
A. Sherstinsky is a scholar working on Signal Processing, Statistical and Nonlinear Physics and Artificial Intelligence, having authored 10 papers that have together received 3.3k indexed citations. Recurring topics across this work include Neural Networks and Applications (5 papers), Image and Signal Denoising Methods (2 papers), Advanced Vision and Imaging (2 papers), Neural Networks Stability and Synchronization (2 papers), Video Coding and Compression Technologies (1 paper), Advanced Data Compression Techniques (1 paper), Neural dynamics and brain function (1 paper) and Visual perception and processing mechanisms (1 paper). The work is most often cited by research in Artificial Intelligence (1.1k citations), Signal Processing (281 citations) and Computer Vision and Pattern Recognition (436 citations). A. Sherstinsky has collaborated with scholars based in United States. Frequent co-authors include Rosalind W. Picard, C.G. Sodini, Brian Richards and R.W. Brodersen. Their work appears in journals such as Physica D Nonlinear Phenomena, IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems, Proceedings - International Conference on Image Processing and IEEE Transactions on Neural Networks.
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.