Experimental demonstration of reservoir computing on a silicon photonics chip

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This paper, published in 1950, received 555 indexed citations. Written by Kristof Vandoorne, Pauline Mechet, Thomas Van Vaerenbergh, Martin Fiers, Geert Morthier, David Verstraeten, Benjamin Schrauwen, Joni Dambre and Peter Bienstman covering the research area of Artificial Intelligence and Electrical and Electronic Engineering. It is primarily cited by scholars working on Artificial Intelligence (520 citations), Electrical and Electronic Engineering (512 citations) and Cognitive Neuroscience (65 citations). Published in Nature Communications.

Countries where authors are citing Experimental demonstration of reservoir computing on a silicon photonics chip

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This map shows the geographic impact of Experimental demonstration of reservoir computing on a silicon photonics chip. 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 Experimental demonstration of reservoir computing on a silicon photonics chip with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Experimental demonstration of reservoir computing on a silicon photonics chip more than expected).

Fields of papers citing Experimental demonstration of reservoir computing on a silicon photonics chip

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Experimental demonstration of reservoir computing on a silicon photonics chip. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Experimental demonstration of reservoir computing on a silicon photonics chip.

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.

This paper is also available at doi.org/10.1038/ncomms4541.

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