Dawn Chen

912 citations
15 papers · 435 · h-index 9

Impact in

Papers in

Dawn Chen

14 papers receiving 424 citations

Peers

Dawn Chen
Comparison fields: 5 of 105
  • Biochemistry 124
  • Parasitology 47
  • Endocrinology, Diabetes and Metabolism 70
  • Computer Vision and Pattern Recognition 65
  • Artificial Intelligence 99
Replace Jennifer Williams with:
Jennifer Williams United Kingdom
Jacob United States
Michael R. Smith Canada
Raphael Zender Germany
Xiaozhen Ye China
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Parikshit Juvekar United States
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Ramon Iovin United States
Dawn Chen relative to Jennifer Williams United Kingdom Jennifer Williams's profile →
Citations per field
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Citations per year

Countries citing papers authored by Dawn Chen

Since Specialization
Citations

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

Fields of papers citing papers by Dawn Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 2009103
2
Which Tasks Should Be Learned Together in Multi-task Learning?
202099
3 201061
4 201060
5 201246
6 202016
7
image2mass: Estimating the Mass of an Object from Its Image
201713
8 201411
9 201610
10 19956
11
Critical Features of Joint Actions that Signal Human Interaction.
20165
12
Learning and Generalization of Abstract Semantic Relations: Preliminary Investigation of Bayesian Approaches
20103
13
Evaluating vector-space models of analogy
20171
14
Generative Inferences Based on a Discriminative Bayesian Model of Relation Learning
20131
15
Enhancing Acquisition of Intuition versus Planning in Problem Solving
20100

About Dawn Chen

Dawn Chen is a scholar working on Artificial Intelligence, Developmental and Educational Psychology, Cultural Studies, Molecular Biology and Computer Vision and Pattern Recognition, having authored 15 papers that have together received 435 indexed citations. Recurring topics across this work include Child and Animal Learning Development (5 papers), Language and cultural evolution (3 papers), Bayesian Modeling and Causal Inference (3 papers), Topic Modeling (3 papers), Natural Language Processing Techniques (2 papers), Eicosanoids and Hypertension Pharmacology (2 papers), Advanced Text Analysis Techniques (2 papers) and Nitric Oxide and Endothelin Effects (1 paper). The work is most often cited by research in Biochemistry (124 citations), Parasitology (47 citations), Endocrinology, Diabetes and Metabolism (70 citations), Computer Vision and Pattern Recognition (65 citations) and Artificial Intelligence (99 citations). Dawn Chen has collaborated with scholars based in United States and France. Frequent co-authors include Hongjing Lu, Keith J. Holyoak, Trevor Standley, Silvio Savarese, Sampath‐Kumar Anandan, Le-Ning Zhang, Yixin Wang, Heather K. Webb, Jon Vincelette and Richard D. Gless. Their work appears in journals such as Cognitive Science, Arteriosclerosis Thrombosis and Vascular Biology, Cellular Microbiology, Cognition and Cognitive Psychology.

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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