James Bradbury

19.6k citations
7 papers · 1.0k indexed · 1 hit paper · h-index 6
Topics
Natural Language Processing Techniques (4 papers)Topic Modeling (4 papers)Climate variability and models (2 papers)
Partner nations
United States

In The Last Decade

James Bradbury

7 papers receiving 927 citations

Hit Papers

Past and future changes in climate and hydrological indic...20062026201220192006200400600

Peers

James Bradbury
Comparison fields: 5 of 74
  • Global and Planetary Change 549
  • Atmospheric Science 292
  • Water Science and Technology 280
  • Ecology 211
  • Nature and Landscape Conservation 140
Replace Pia Papadopol with:
Pia Papadopol Canada
Ron F. Hopkinson Canada
Phillip A. Pasteris United States
Gregory L. Johnson United States
Monica Petri Netherlands
Douglas I. Moore United States
Joseph M. Caprio United States
Guillermo N. Murray‐Tortarolo Mexico
Miriam Machwitz Germany
Steven T. Brantley United States
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Citations per field
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Citations per year

Countries citing papers authored by James Bradbury

Since Specialization
Citations

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

Fields of papers citing papers by James Bradbury

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Bradbury

This figure shows the co-authorship network connecting the top 25 collaborators of James Bradbury. A scholar is included among the top collaborators of James Bradbury based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with James Bradbury. James Bradbury is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

7 of 7 papers shown
#WorkIndexed citations
1 6
2
On Machine Learning and Programming Languages
6
3
Towards the ImageNet-CNN of NLP: Pretraining Sentence Encoders with Machine Translation
1
4
Non-Autoregressive Neural Machine Translation
55
5 10
6 205
7
Past and future changes in climate and hydrological indicators in the US Northeastbreakdown →
719

About James Bradbury

James Bradbury is a scholar working on Artificial Intelligence, Atmospheric Science and Global and Planetary Change, having authored 7 papers that have together received 1.0k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (4 papers), Topic Modeling (4 papers) and Climate variability and models (2 papers). The work is most often cited by research in Global and Planetary Change (549 citations), Ecological Modeling (92 citations) and Water Science and Technology (280 citations). James Bradbury has collaborated with scholars based in United States. Frequent co-authors include Bruce T. Anderson, Cameron P. Wake, Katharine Hayhoe, Art Degaetano, Tara J. Troy, Lifeng Luo, David W. Wolfe, Thomas G. Huntington, Justin Sheffield and Mark D. Schwartz. Their work appears in journals such as Climate Dynamics, Mitigation and Adaptation Strategies for Global Change and arXiv (Cornell University).

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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