Daphna Buchsbaum

46 papers receiving 841 citations

Peers

Daphna Buchsbaum
Comparison fields: 5 of 64
  • Developmental and Educational Psychology 360
  • General Decision Sciences 45
  • Social Psychology 230
  • Experimental and Cognitive Psychology 91
  • Cognitive Neuroscience 99
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Citations per year

Countries citing papers authored by Daphna Buchsbaum

Since Specialization
Citations

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

Fields of papers citing papers by Daphna Buchsbaum

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005186
2 2011167
3 2012121
4 201642
5 201441
6 201737
7 201633
8 201532
9 200627
10 201827
11 202321
12 201818
13 202116
14
Segmenting and Recognizing Human Action using Low-level Video Features
201111
15 202210
16
Do I know that you know what you know? Modeling testimony in causal inference
20129
17
When does the majority rule? Preschoolers’ trust in majority informants varies by task domain
20139
18 20228
19 20238
20
Learning from Actions and their Consequences: Inferring Causal Variables from Continuous Sequences of Human Action
20097

About Daphna Buchsbaum

Daphna Buchsbaum is a scholar working on Developmental and Educational Psychology, Social Psychology, Genetics, Artificial Intelligence and Human-Computer Interaction, having authored 49 papers that have together received 912 indexed citations. Recurring topics across this work include Child and Animal Learning Development (30 papers), Human-Animal Interaction Studies (8 papers), Social Robot Interaction and HRI (6 papers), Bayesian Modeling and Causal Inference (6 papers), Categorization, perception, and language (2 papers), Decision-Making and Behavioral Economics (2 papers), Evolutionary Algorithms and Applications (2 papers) and Epistemology, Ethics, and Metaphysics (2 papers). The work is most often cited by research in Developmental and Educational Psychology (360 citations), General Decision Sciences (45 citations), Social Psychology (230 citations), Experimental and Cognitive Psychology (91 citations) and Cognitive Neuroscience (99 citations). Daphna Buchsbaum has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Alison Gopnik C, Thomas L. Griffiths, Bruce M. Blumberg, Cynthia Breazeal, Patrick Shafto, Sophie Bridgers, Jesse Gray, Deena Skolnick Weisberg, Andrew Whalen and Stephanie Denison. Their work appears in journals such as Cognitive Science, Animal Cognition, Developmental Psychology, Journal of Experimental Psychology General and Philosophical Transactions of the Royal Society B Biological 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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