Machine Learning Science and Technology

6.7k citations
902 papers · · active since 1954

Impact in

Papers in

Machine Learning Science and Technology

730 papers receiving 6.5k citations

Peers

Machine Learning Science and Technology
Comparison fields: 5 of 181
  • Computational Mathematics 74
  • Structural Biology 114
  • Computational Theory and Mathematics 1.1k
  • Artificial Intelligence 1.7k
  • Materials Chemistry 2.1k
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Machine Learning Science and Technology relative to Journal of Mathematical Imaging and Vision France Journal of Mathematical Imaging and Vision's profile →
Citations per field
00.5×11.5×
Journal of Mathematical Imaging and Vision · 1×
Citations per year

Countries where authors publish in Machine Learning Science and Technology

Since Specialization
Citations

This map shows the geographic impact of research published in Machine Learning Science and Technology. 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 papers published in Machine Learning Science and Technology with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Machine Learning Science and Technology more than expected).

Fields of papers published in Machine Learning Science and Technology

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Machine Learning Science and Technology. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Machine Learning Science and Technology.

About Machine Learning Science and Technology

The 902 papers published in Machine Learning Science and Technology in the last decades have received a total of 6.7k indexed citations . Papers published in Machine Learning Science and Technology usually cover Computational Mathematics (10 papers), Artificial Intelligence (342 papers), Structural Biology (14 papers), Statistical and Nonlinear Physics (100 papers) and Computational Theory and Mathematics (109 papers) specifically the topics of Machine Learning in Materials Science (210 papers), Computational Drug Discovery Methods (79 papers), Model Reduction and Neural Networks (72 papers), Quantum Computing Algorithms and Architecture (67 papers), Neural Networks and Applications (67 papers), Gaussian Processes and Bayesian Inference (51 papers), Computational Physics and Python Applications (45 papers) and Protein Structure and Dynamics (44 papers). The most active scholars publishing in Machine Learning Science and Technology are Sergei Manzhos, Esben Jannik Bjerrum, Haoyan Huo, Matthias Rupp, Teodoro Laino, Philippe Schwaller, Alain C. Vaucher, Jean‐Louis Reymond, Jiazhen He and O. Anatole von Lilienfeld.

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.

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