Ralf Mayrhofer

473 citations
26 papers · 290 · h-index 10

Impact in

Papers in

Ralf Mayrhofer

26 papers receiving 263 citations

Peers

Ralf Mayrhofer
Comparison fields: 5 of 48
  • General Decision Sciences 71
  • Developmental and Educational Psychology 164
  • History and Philosophy of Science 41
  • Family Practice 12
  • Artificial Intelligence 148
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Citations per year

Countries citing papers authored by Ralf Mayrhofer

Since Specialization
Citations

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

Fields of papers citing papers by Ralf Mayrhofer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside Ralf Mayrhofer, 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 Ralf Mayrhofer Line = papers co-authored together Ralf Mayrhofer links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201452
2 201435
3 201827
4 201722
5 201517
6
Structured Correlation from the Causal Background
200814
7
Agents and Causes: A Bayesian Error Attribution Model of Causal Reasoning
201014
8 201613
9 202013
10 201412
11
Heuristics in Covariation-based Induction of Causal Models: Sufficiency and Necessity Priors
201110
12 201810
13
A Rational Model of Elemental Diagnostic Inference
20097
14 20217
15 20227
16
Causal learning from interventions and dynamics in continuous time.
20176
17 20154
18 20123
19
Agency Intuitions in Physical Interactions
20133
20
Sequential Diagnostic Reasoning with Verbal Information
20133

About Ralf Mayrhofer

Ralf Mayrhofer is a scholar working on Developmental and Educational Psychology, Artificial Intelligence, General Decision Sciences, History and Philosophy of Science and Experimental and Cognitive Psychology, having authored 26 papers that have together received 290 indexed citations. Recurring topics across this work include Child and Animal Learning Development (18 papers), Bayesian Modeling and Causal Inference (17 papers), Cognitive Science and Mapping (5 papers), Decision-Making and Behavioral Economics (5 papers), Philosophy and History of Science (5 papers), Logic, Reasoning, and Knowledge (3 papers), Advanced Text Analysis Techniques (3 papers) and Memory and Neural Mechanisms (2 papers). The work is most often cited by research in General Decision Sciences (71 citations), Developmental and Educational Psychology (164 citations), History and Philosophy of Science (41 citations), Family Practice (12 citations) and Artificial Intelligence (148 citations). Ralf Mayrhofer has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Michael R. Waldmann, Björn Meder, Neil R Bramley, Tobias Gerstenberg, David A. Lagnado, York Hagmayer, Noah D. Goodman, Josh Tenenbaum, Ben Deverett and Charles Kemp. Their work appears in journals such as Cognitive Science, Cognitive Psychology, Cognition, Topics in Cognitive Science and Psychonomic Bulletin & Review.

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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