Kevin A. Smith

56 papers receiving 764 citations

Peers

Kevin A. Smith
Comparison fields: 5 of 130
  • General Decision Sciences 36
  • Cognitive Neuroscience 200
  • Experimental and Cognitive Psychology 107
  • Developmental and Educational Psychology 106
  • Social Psychology 119
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Countries citing papers authored by Kevin A. Smith

Since Specialization
Citations

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

Fields of papers citing papers by Kevin A. Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin A. Smith. 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 Kevin A. Smith. The network helps show where Kevin A. Smith may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1
End-to-End Differentiable Physics for Learning and Control
2018131
2 201395
3 201364
4
Defining aircrew coordination: Searching mishaps for meaning
198957
5 200844
6 199939
7 200930
8
Consistent physics underlying ballistic motion prediction
201329
9
Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations
201927
10 201524
11 201123
12 201820
13
Empirical Evidence for Markov Chain Monte Carlo in Memory Search.
201418
14 201116
15 202115
16 202114
17
Physical predictions over time
201314
18 200713
19 201111
20
Coupled Relap5 and Contain accident analysis using PVM
199510

About Kevin A. Smith

Kevin A. Smith is a scholar working on Artificial Intelligence, Developmental and Educational Psychology, Computer Vision and Pattern Recognition, Social Psychology and Mechanics of Materials, having authored 62 papers that have together received 818 indexed citations. Recurring topics across this work include Child and Animal Learning Development (9 papers), Decision-Making and Behavioral Economics (6 papers), Action Observation and Synchronization (4 papers), Material Properties and Processing (4 papers), Human Pose and Action Recognition (3 papers), Engineering Applied Research (3 papers), Gaussian Processes and Bayesian Inference (3 papers) and Hydraulic Fracturing and Reservoir Analysis (3 papers). The work is most often cited by research in General Decision Sciences (36 citations), Cognitive Neuroscience (200 citations), Experimental and Cognitive Psychology (107 citations), Developmental and Educational Psychology (106 citations) and Social Psychology (119 citations). Kevin A. Smith has collaborated with scholars based in United States, United Kingdom and Poland. Frequent co-authors include Edward Vul, David E. Huber, Josh Tenenbaum, Kelsey R. Allen, J. Zico Kolter, John A. Carrino, Charmine E. J. Härtel, Peter Battaglia, Joshua B. Tenenbaum and Tomer Ullman. Their work appears in journals such as Cognitive Science, SAE technical papers on CD-ROM/SAE technical paper series, Michigan Law Review, Journal of Experimental Psychology General and Cognitive Neuropsychology.

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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