Daniel Silver

3.1k citations
149 papers · 2.0k · h-index 24

Impact in

    • Cultural Industries and Urban Development
    • Domain Adaptation and Few-Shot Learning
    • Neural Networks and Applications
    • Machine Learning and Algorithms
    • Machine Learning and ELM

Papers in

Daniel Silver

136 papers receiving 1.8k citations

Peers

Daniel Silver
Comparison fields: 5 of 159
  • Urban Studies 217
  • Artificial Intelligence 601
  • Transportation 95
  • Sociology and Political Science 588
  • Music 42
Replace Steven Gregory with:
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Daniel Silver relative to Steven Gregory United Kingdom Steven Gregory's profile →
Citations per field
00.5×3.5×
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Citations per year

Countries citing papers authored by Daniel Silver

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Silver

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 149 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Lifelong Machine Learning Systems: Beyond Learning Algorithms
2013162
2 197392
3 201091
4 200284
5 201084
6 201581
7 199655
8
The View of Life: Four Metaphysical Essays with Journal Aphorisms
201155
9 201153
10 199652
11 201646
12 197844
13
The Politics of Urban Cultural Policy: Global Perspectives
201240
14 201438
15 200830
16
Selective transfer of neural network task knowledge
200030
17
Keystroke and Eye-Tracking Biometrics for User Identification.
200628
18 200726
19 201926
20 201226

About Daniel Silver

Daniel Silver is a scholar working on Sociology and Political Science, Artificial Intelligence, Urban Studies, Computer Vision and Pattern Recognition and Clinical Psychology, having authored 149 papers that have together received 2.0k indexed citations. Recurring topics across this work include Social and Cultural Dynamics (27 papers), Domain Adaptation and Few-Shot Learning (21 papers), Neural Networks and Applications (15 papers), Cultural Industries and Urban Development (13 papers), Urban Design and Spatial Analysis (10 papers), Land Use and Ecosystem Services (10 papers), Machine Learning and ELM (9 papers) and Urban, Neighborhood, and Segregation Studies (8 papers). The work is most often cited by research in Urban Studies (217 citations), Artificial Intelligence (601 citations), Transportation (95 citations), Sociology and Political Science (588 citations) and Music (42 citations). Daniel Silver has collaborated with scholars based in Canada, United States and Brazil. Frequent co-authors include Robert E. Mercer, Terry Nichols Clark, Qiang Yang, Lianghao Li, Donald N. Levine, J. A. Andrews, Georg Simmel, Monica Lee, Howard E. Book and Joel Sadavoy. Their work appears in journals such as The Canadian Journal of Psychiatry, American Scientist, PLoS ONE, Cities and European Journal of Sociology.

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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