Ryan Rifkin
- Molecular Biology top 5%
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 1%
- Cancer Research top 10%
- Signal Processing top 5%
- Co-authors
- Aldebaro KlautauSayan MukherjeeTomaso PoggioJill P. MesirovPablo TamayoTodd R. GolubEric S. LanderMichael Reich
- Topics
- Gene expression and cancer classification (7 papers)Sparse and Compressive Sensing Techniques (5 papers)Neural Networks and Applications (5 papers)
- Partner nations
- United StatesJapanLebanon
In The Last Decade
Ryan Rifkin
24 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 181
- Molecular Biology 1.6k
- Artificial Intelligence 1.4k
- Computer Vision and Pattern Recognition 810
- Cancer Research 281
- Signal Processing 230
Countries citing papers authored by Ryan Rifkin
This map shows the geographic impact of Ryan Rifkin'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 Ryan Rifkin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryan Rifkin more than expected).
Fields of papers citing papers by Ryan Rifkin
This network shows the impact of papers produced by Ryan Rifkin. 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 Ryan Rifkin. The network helps show where Ryan Rifkin may publish in the future.
Co-authorship network of co-authors of Ryan Rifkin
This figure shows the co-authorship network connecting the top 25 collaborators of Ryan Rifkin. A scholar is included among the top collaborators of Ryan Rifkin 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 Ryan Rifkin. Ryan Rifkin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 39 | |
| 2 | AClass: A simple, online, parallelizable algorithm for probabilistic classification | 4 |
| 3 | Notes on Regularized Least Squares | 66 |
| 4 | Phonetic Classification Using Hierarchical, Feed-forward, Spectro-temporal Patch-based Architectures | 8 |
| 5 | 2 | |
| 6 | 103 | |
| 7 | In Defense of One-Vs-All Classificationbreakdown → | 967 |
| 8 | 173 | |
| 9 | 194 | |
| 10 | 13 | |
| 11 | 118 | |
| 12 | 47 | |
| 13 | 5 | |
| 14 | 50 | |
| 15 | Support Vector Machine Classification of Microarray Data | 122 |
| 16 | The Audiomomma Music Recommendation System | 1 |
| 17 | Multiclass cancer diagnosis using tumor gene expression signaturesbreakdown → | 1458 |
| 18 | The Static Stochastic Ground Holding Problem with Aggregate Demands | 10 |
| 19 | From Regression to Classication in Support Vector Machines | 2 |
| 20 | From Regression to Classification in Support Vector Machines | 16 |
About Ryan Rifkin
Ryan Rifkin is a scholar working on Signal Processing, Artificial Intelligence and Music, having authored 25 papers that have together received 3.8k indexed citations. Recurring topics across this work include Gene expression and cancer classification (7 papers), Sparse and Compressive Sensing Techniques (5 papers) and Neural Networks and Applications (5 papers). The work is most often cited by research in Artificial Intelligence (1.4k citations), Computer Vision and Pattern Recognition (810 citations) and Molecular Biology (1.6k citations). Ryan Rifkin has collaborated with scholars based in United States, Japan and Lebanon. Frequent co-authors include Aldebaro Klautau, Sayan Mukherjee, Tomaso Poggio, Jill P. Mesirov, Pablo Tamayo, Todd R. Golub, Eric S. Lander, Michael Reich, Sridhar Ramaswamy and William L. Gerald. Their work appears in journals such as Proceedings of the National Academy of Sciences, Bioinformatics and Nature Cell Biology.
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.