Rie Johnson
- Artificial Intelligence top 0.5%
- Topic Modeling 3
- Text and Document Classification Technologies 3
- Natural Language Processing Techniques 2
- Computational Mechanics top 2%
- Sparse and Compressive Sensing Techniques 1
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- Generative Adversarial Networks and Image Synthesis 2
- Face and Expression Recognition 2
- Digital Media Forensic Detection 2
- Numerical Analysis top 10%
- Statistics and Probability top 5%
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- Model Reduction and Neural Networks 2
- Co-authors
- Tong ZhangLakhmi C. JainAnni CodenGuergana SavovaPiet C. de GroenPhilip V. OgrenChristopher G. Chute
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (2 papers)Journal of Biomedical Informatics (1 paper)Journal of Machine Learning Research (1 paper)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Rie Johnson
11 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 133
- Artificial Intelligence 1.8k
- Computational Mechanics 421
- Computer Vision and Pattern Recognition 301
- Numerical Analysis 70
- Statistics and Probability 105
Countries citing papers authored by Rie Johnson
This map shows the geographic impact of Rie Johnson'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 Rie Johnson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rie Johnson more than expected).
Fields of papers citing papers by Rie Johnson
This network shows the impact of papers produced by Rie Johnson. 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 Rie Johnson. The network helps show where Rie Johnson may publish in the future.
Co-authorship network
The 10 scholars most cited alongside Rie Johnson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 0 | |
| 2 | 2019 | 12 | |
| 3 | Composite Functional Gradient Learning of Generative Adversarial Models | 2018 | 1 |
| 4 | Deep Pyramid Convolutional Neural Networks for Text Categorizationbreakdown → | 2017 | 511 |
| 5 | Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding. | 2015 | 94 |
| 6 | Effective Use of Word Order for Text Categorization with Convolutional Neural Networksbreakdown → | 2015 | 465 |
| 7 | Accelerating Stochastic Gradient Descent using Predictive Variance Reductionbreakdown → | 2013 | 800 |
| 8 | 2013 | 121 | |
| 9 | 2008 | 56 | |
| 10 | 2008 | 54 | |
| 11 | On the Effectiveness of Laplacian Normalization for Graph Semi-supervised Learning | 2007 | 41 |
| 12 | Neural Network Training Using Genetic Algorithms | 1996 | 146 |
About Rie Johnson
Rie Johnson is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Statistical and Nonlinear Physics, Computational Mechanics and Molecular Biology, having authored 12 papers that have together received 2.3k indexed citations. Recurring topics across this work include Topic Modeling (3 papers), Text and Document Classification Technologies (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Face and Expression Recognition (2 papers), Digital Media Forensic Detection (2 papers), Model Reduction and Neural Networks (2 papers), Natural Language Processing Techniques (2 papers) and Sparse and Compressive Sensing Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (1.8k citations), Computational Mechanics (421 citations), Computer Vision and Pattern Recognition (301 citations), Numerical Analysis (70 citations) and Statistics and Probability (105 citations). Rie Johnson has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Tong Zhang, Tong Zhang, Lakhmi C. Jain, Tong Zhang, Tong Zhang, Anni Coden, Guergana Savova, Piet C. de Groen, Philip V. Ogren and Christopher G. Chute. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Biomedical Informatics, Journal of Machine Learning Research, IEEE Transactions on Information Theory and PubMed.
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.