Neil R Bramley

925 citations
49 papers · 400 indexed · h-index 10

Neil R Bramley

44 papers receiving 376 citations

Peers

Neil R Bramley
Comparison fields: 5 of 56
  • General Decision Sciences 74
  • Developmental and Educational Psychology 211
  • History and Philosophy of Science 34
  • Artificial Intelligence 197
  • Cognitive Neuroscience 102
Replace Walter Schroyens with:
Walter Schroyens Belgium
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Citations per year

Countries citing papers authored by Neil R Bramley

Since Specialization
Citations

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

Fields of papers citing papers by Neil R Bramley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Neil R Bramley. 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 Neil R Bramley. The network helps show where Neil R Bramley may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Neil R Bramley, 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 Neil R Bramley Line = papers co-authored together Neil R Bramley links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20242
4 20235
5 202211
6
Symbolic and Sub-Symbolic Systems in People and Machines
20211
7
Know your network: Sensitivity to structure in social learning
20211
8
Bayesian Experimental Design for Intractable Models of Cognition
20211
9
Learning hidden causal structure from temporal data
20201
10
Belief revision in a micro-social network: Modeling sensitivity to statistical dependencies in social learning
20205
11 20192
12
The critical moment is coming: Modeling the dynamics of suspense.
20191
13 20182
14
A causal model approach to dynamic control
20180
15
Grounding Compositional Hypothesis Generation in Specific Instances.
20186
16
Causal structure learning with continuous variables in continuous time
20181
17
Children's Causal Interventions Combine Discrimination and Confirmation.
20188
18
Beliefs about sparsity affect causal experimentation
20172
19
Natural science: Active learning in dynamic physical microworlds.
20164
20
Staying afloat on Neurath's boat: Heuristics for sequential causal learning
20156

About Neil R Bramley

Neil R Bramley is a scholar working on General Decision Sciences, Developmental and Educational Psychology and History and Philosophy of Science, having authored 49 papers that have together received 400 indexed citations. Recurring topics across this work include Child and Animal Learning Development (25 papers), Bayesian Modeling and Causal Inference (17 papers), Decision-Making and Behavioral Economics (7 papers), Evolutionary Algorithms and Applications (7 papers), Philosophy and History of Science (7 papers), Machine Learning and Algorithms (5 papers), Cognitive Science and Mapping (5 papers) and Opinion Dynamics and Social Influence (4 papers). The work is most often cited by research in General Decision Sciences (74 citations), Developmental and Educational Psychology (211 citations) and History and Philosophy of Science (34 citations). Neil R Bramley has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include David A. Lagnado, Todd M. Gureckis, Tobias Gerstenberg, Peter Dayan, Maarten Speekenbrink, Thomas L. Griffiths, Ernest Davis, Christopher G. Lucas, Joshua B. Tenenbaum and Ralf Mayrhofer. Their work appears in journals such as Nature Communications, Psychological Review and Psychological Science.

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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