Robert Salzmann

807 citations
8 papers · 468 · 1 hit paper · h-index 6

Impact in

Papers in

Robert Salzmann

7 papers receiving 440 citations

Hit Papers

Training deep quantum neural networks 2020 · 388 citations
3880+2+4Years since publication100200300

Peers

Robert Salzmann
Comparison fields: 5 of 75
  • Artificial Intelligence 354
  • Computational Theory and Mathematics 66
  • Management Science and Operations Research 50
  • Demography 46
  • Atomic and Molecular Physics, and Optics 95
Replace Enrique Lizaso with:
Enrique Lizaso Spain
Samuel Mugel Spain
Faisal Shah Khan United Arab Emirates
Xiaoyuan Liu United States
Gili Rosenberg United States
Werner Schachinger Austria
Gadi Aleksandrowicz Israel
Mohammed Zidan Egypt
Enjian Bai China
Robert Salzmann relative to Enrique Lizaso Spain Enrique Lizaso's profile →
Citations per field
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Citations per year

Countries citing papers authored by Robert Salzmann

Since Specialization
Citations

This map shows the geographic impact of Robert Salzmann'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 Robert Salzmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Salzmann more than expected).

Fields of papers citing papers by Robert Salzmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robert Salzmann. 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 Robert Salzmann. The network helps show where Robert Salzmann may publish in the future.

Co-authors

The 13 scholars most cited alongside Robert Salzmann, 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 Robert Salzmann Line = papers co-authored together Robert Salzmann links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown

About Robert Salzmann

Robert Salzmann is a scholar working on Artificial Intelligence, Economics and Econometrics, Computational Theory and Mathematics, Management Science and Operations Research and Demography, having authored 8 papers that have together received 468 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (4 papers), Quantum Computing Algorithms and Architecture (4 papers), Insurance and Financial Risk Management (2 papers), Probability and Risk Models (2 papers), Insurance, Mortality, Demography, Risk Management (2 papers), Quantum chaos and dynamical systems (1 paper), Spectral Theory in Mathematical Physics (1 paper) and Computability, Logic, AI Algorithms (1 paper). The work is most often cited by research in Artificial Intelligence (354 citations), Computational Theory and Mathematics (66 citations), Management Science and Operations Research (50 citations), Demography (46 citations) and Atomic and Molecular Physics, and Optics (95 citations). Robert Salzmann has collaborated with scholars based in United Kingdom, Switzerland and United States. Frequent co-authors include Dmytro Bondarenko, Terry Farrelly, Kerstin Beer, Tobias J. Osborne, Ramona Wolf, Mario V. Wüthrich, Nilanjana Datta, Mark M. Wilde, Xin Wang and Gilad Gour. Their work appears in journals such as Foundations of Computational Mathematics, Nature Communications, New Journal of Physics, IEEE Transactions on Information Theory and Astin Bulletin.

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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