A Tutorial on Energy-Based Learning

401 indexed citations
published 2006

Impact in

Classified as

Authors
Yann LeCunSumit ChopraRaia HadsellFu Jie Huang

In The Last Decade

doi.org/w58890593 →

Countries where authors are citing A Tutorial on Energy-Based Learning

Specialization
Citations

This map shows the geographic impact of A Tutorial on Energy-Based Learning. 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 Tutorial on Energy-Based Learning with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A Tutorial on Energy-Based Learning more than expected).

Fields of papers citing A Tutorial on Energy-Based Learning

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of A Tutorial on Energy-Based Learning. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the A Tutorial on Energy-Based Learning.

About A Tutorial on Energy-Based Learning

This paper, published in 2006, received 401 indexed citations . Written by Yann LeCun, Sumit Chopra, Raia Hadsell and Fu Jie Huang covering the research area of Artificial Intelligence and Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Artificial Intelligence (239 citations), Computer Vision and Pattern Recognition (206 citations), Signal Processing (35 citations), Statistical and Nonlinear Physics (29 citations) and Control and Systems Engineering (26 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.

This paper is also available at doi.org/w58890593.

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