Tom Claassen

956 citations
37 papers · 373 · h-index 12

Impact in

Papers in

Tom Claassen

34 papers receiving 351 citations

Peers

Tom Claassen
Comparison fields: 5 of 90
  • Psychiatry and Mental health 97
  • Cognitive Neuroscience 100
  • Artificial Intelligence 144
  • Statistics and Probability 34
  • Health Informatics 5
Replace Antonio Calcagnì with:
Antonio Calcagnì Italy
Sara van Erp Netherlands
Eric V. Strobl United States
David Marc Anton Mehler Germany
Alex Kale United States
Gabriela Stegmann United States
Maarten L. Wijnants Netherlands
Danilo Fum Italy
Eric G. Freedman United States
Tongran Liu China
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Citations per field
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Antonio Calcagnì · 1×
Citations per year

Countries citing papers authored by Tom Claassen

Since Specialization
Citations

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

Fields of papers citing papers by Tom Claassen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201791
2
Joint Causal Inference from Multiple Contexts
202028
3 201325
4 201724
5 201624
6 201223
7
Causal discovery in multiple models from different experiments
201018
8 202018
9 201516
10 201816
11 201214
12 201811
13 20169
14 20248
15 20207
16 20177
17
Learning causal network structure from multiple (in)dependence models
20104
18
Bayesian probabilities for constraint-based causal discovery
20134
19
A structure independent algorithm for causal discovery
20114
20
Arrowhead completeness from minimal conditional independencies
20103

About Tom Claassen

Tom Claassen is a scholar working on Artificial Intelligence, Psychiatry and Mental health, Cognitive Neuroscience, Management Science and Operations Research and Statistics and Probability, having authored 37 papers that have together received 373 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (21 papers), Attention Deficit Hyperactivity Disorder (6 papers), AI-based Problem Solving and Planning (4 papers), Multi-Criteria Decision Making (4 papers), Neural and Behavioral Psychology Studies (4 papers), Advanced Causal Inference Techniques (3 papers), Logic, Reasoning, and Knowledge (3 papers) and Rough Sets and Fuzzy Logic (3 papers). The work is most often cited by research in Psychiatry and Mental health (97 citations), Cognitive Neuroscience (100 citations), Artificial Intelligence (144 citations), Statistics and Probability (34 citations) and Health Informatics (5 citations). Tom Claassen has collaborated with scholars based in Netherlands, United States and Indonesia. Frequent co-authors include Tom Heskes, Joris M. Mooij, P. Groot, Jan K. Buitelaar, Jeffrey Glennon, Sara Magliacane, Nanda Rommelse, Anoek M. Oerlemans, Catharina A. Hartman and Barbara Franke. Their work appears in journals such as European Neuropsychopharmacology, Scientific Reports, Frontiers in Psychiatry, International Journal of Approximate Reasoning and Frontiers in Ecology and Evolution.

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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