Mathias Sablé-Meyer

14 papers receiving 327 citations

Mathias Sablé-Meyer's Hit Papers

Symbols and mental programs: a hypothesis about human singularity 2022 · 81 citations
810+1+2Years since publication255075

Peers

Mathias Sablé-Meyer
Comparison fields: 5 of 64
  • Statistics and Probability 47
  • Developmental and Educational Psychology 67
  • Cognitive Neuroscience 78
  • Software 17
  • General Decision Sciences 7
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Citations per field
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Citations per year

Countries citing papers authored by Mathias Sablé-Meyer

Since Specialization
Citations

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

Fields of papers citing papers by Mathias Sablé-Meyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mathias Sablé-Meyer. 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 Mathias Sablé-Meyer. The network helps show where Mathias Sablé-Meyer may publish in the future.

Co-authors

The 21 scholars most cited alongside Mathias Sablé-Meyer, 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 Mathias Sablé-Meyer Line = papers co-authored together Mathias Sablé-Meyer links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1
Symbols and mental programs: a hypothesis about human singularity
Hit paper breakdown →
202281
2 202161
3 202154
4 202334
5 202229
6
Learning Libraries of Subroutines for Neurally–Guided Bayesian Program Induction
201822
7 202217
8 202112
9
Library learning for neurally-guided Bayesian program induction
20188
10 20257
11 20235
12 20244
13
Assessing the role of matching bias in reasoning with disjunctions.
20192
14 20251
15 20250
16 20260

About Mathias Sablé-Meyer

Mathias Sablé-Meyer is a scholar working on Statistics and Probability, Developmental and Educational Psychology, General Decision Sciences, Artificial Intelligence and Information Systems, having authored 16 papers that have together received 337 indexed citations. Recurring topics across this work include Child and Animal Learning Development (5 papers), Cognitive and developmental aspects of mathematical skills (5 papers), Software Engineering Research (3 papers), Machine Learning and Algorithms (3 papers), Evolutionary Algorithms and Applications (2 papers), Decision-Making and Behavioral Economics (2 papers), History and Theory of Mathematics (1 paper) and Machine Learning and Data Classification (1 paper). The work is most often cited by research in Statistics and Probability (47 citations), Developmental and Educational Psychology (67 citations), Cognitive Neuroscience (78 citations), Software (17 citations) and General Decision Sciences (7 citations). Mathias Sablé-Meyer has collaborated with scholars based in France, United States and United Kingdom. Frequent co-authors include Stanislas Dehaene, Josh Tenenbaum, Kevin Ellis, Armando Solar-Lezama, Fosca Al Roumi, Samuel Planton, Yair Lakretz, Luke Hewitt, Maxwell Nye and Serge Caparos. Their work appears in journals such as Trends in Cognitive Sciences, Cognition, Journal of Neuroscience, Cognitive Psychology and Review of Philosophy and Psychology.

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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