Dawn Chen

901 citations
15 papers · 434 indexed · h-index 9

Dawn Chen

14 papers receiving 423 citations

Peers

Dawn Chen
Comparison fields: 5 of 105
  • Biochemistry 126
  • Parasitology 49
  • Endocrinology, Diabetes and Metabolism 88
  • Computer Vision and Pattern Recognition 66
  • Artificial Intelligence 100
Replace Pooja Sharma with:
Pooja Sharma India
Christian Spieth Germany
Michael R. Smith Canada
Jacob United States
Raphael Zender Germany
Xiaozhen Ye China
Seongmin Lee South Korea
Patricia Ordóñez United States
Ruiguo Li China
Dawn Chen relative to Pooja Sharma India Pooja Sharma's profile →
Citations per field
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Pooja Sharma · 1×
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-authorship network

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
Which Tasks Should Be Learned Together in Multi-task Learning?
202099
2 202015
3
image2mass: Estimating the Mass of an Object from Its Image
201713
4
Evaluating vector-space models of analogy
20171
5
Critical Features of Joint Actions that Signal Human Interaction.
20165
6 201610
7 201411
8
Generative Inferences Based on a Discriminative Bayesian Model of Relation Learning
20131
9 201246
10
Enhancing Acquisition of Intuition versus Planning in Problem Solving
20100
11
Learning and Generalization of Abstract Semantic Relations: Preliminary Investigation of Bayesian Approaches
20103
12 201060
13 201061
14 2009103
15 19956

About Dawn Chen

Dawn Chen is a scholar working on Developmental and Educational Psychology, Cultural Studies, Biochemistry, Artificial Intelligence and Experimental and Cognitive Psychology, having authored 15 papers that have together received 434 indexed citations. Recurring topics across this work include Child and Animal Learning Development (5 papers), Bayesian Modeling and Causal Inference (3 papers), Topic Modeling (3 papers), Language and cultural evolution (3 papers), Advanced Text Analysis Techniques (2 papers), Eicosanoids and Hypertension Pharmacology (2 papers), Natural Language Processing Techniques (2 papers) and Hormonal Regulation and Hypertension (2 papers). The work is most often cited by research in Biochemistry (126 citations), Parasitology (49 citations), Endocrinology, Diabetes and Metabolism (88 citations), Computer Vision and Pattern Recognition (66 citations) and Artificial Intelligence (100 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, Yixin Wang, Sampath‐Kumar Anandan, Heather K. Webb, Jon Vincelette, Le-Ning Zhang and Richard D. Gless. Their work appears in journals such as Cognitive Science, Psychological Review, Arteriosclerosis Thrombosis and Vascular Biology, Bioorganic & Medicinal Chemistry Letters 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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