Mathias Sablé-Meyer

14 papers receiving 275 citations

Hit Papers

Symbols and mental programs: a hypothesis about human singularity 2022 · 72 citations
720+1+2Years since publication204060

Peers

Mathias Sablé-Meyer
Comparison fields: 5 of 60
  • Developmental and Educational Psychology 65
  • Statistics and Probability 38
  • Theoretical Computer Science 5
  • Software 17
  • General Decision Sciences 7
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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 19 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 →
202272
2 202147
3 202144
4 202328
5 202225
6
Learning Libraries of Subroutines for Neurally–Guided Bayesian Program Induction
201817
7 202215
8 202110
9
Library learning for neurally-guided Bayesian program induction
20189
10 20245
11 20255
12 20233
13
Assessing the role of matching bias in reasoning with disjunctions.
20192
14 20251
15 20260
16 20250

About Mathias Sablé-Meyer

Mathias Sablé-Meyer is a scholar working on Artificial Intelligence, Developmental and Educational Psychology, Statistics and Probability, Information Systems and Cognitive Neuroscience, having authored 16 papers that have together received 283 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), Decision-Making and Behavioral Economics (2 papers), Evolutionary Algorithms and Applications (2 papers), Cognitive Science and Education Research (1 paper) and Mental Health Research Topics (1 paper). The work is most often cited by research in Developmental and Educational Psychology (65 citations), Statistics and Probability (38 citations), Theoretical Computer Science (5 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, Kevin Ellis, Yair Lakretz, Samuel Planton, Armando Solar-Lezama, Joshua B. Tenenbaum, Josh Tenenbaum, Serge Caparos, Luke Hewitt and Maxwell Nye. Their work appears in journals such as Journal of Neuroscience, Trends in Cognitive Sciences, Cognition, Scientific Reports and Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences.

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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