Irina Rish
Impact in
- Software top 2%
- Artificial Intelligence top 0.5%
- Bayesian Modeling and Causal Inference
- Anomaly Detection Techniques and Applications
Papers in
-
- Bayesian Modeling and Causal Inference 20
- Machine Learning and Algorithms 11
- Data Stream Mining Techniques 7
- Neural Networks and Applications 6
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- Software System Performance and Reliability 9
- Co-authors
- Rina Dechter (7 shared papers)Genady Ya. Grabarnik (7 shared papers)Alina Beygelzimer (9 shared papers)Guillermo Cecchi (23 shared papers)S. Ma (4 shared papers)G. Grinstein (2 shared papers)Ralph Linsker (2 shared papers)Marc Brodie (4 shared papers)
- Journals
- IBM Journal of Research and Development (3 papers)PLoS ONE (2 papers)Scientific Reports (2 papers)Journal of Vision (1 paper)Schizophrenia (1 paper)
- Partner nations
- United StatesCanadaFrance
In The Last Decade
Irina Rish
80 papers receiving 3.3k citations
Irina Rish's Hit Papers
Peers
Comparison fields: 5 of 188
- Software 185
- Artificial Intelligence 1.5k
- Computer Networks and Communications 904
- Signal Processing 352
- Health Information Management 117
Countries citing papers authored by Irina Rish
This map shows the geographic impact of Irina Rish'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 Irina Rish with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Irina Rish more than expected).
Fields of papers citing papers by Irina Rish
This network shows the impact of papers produced by Irina Rish. 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 Irina Rish. The network helps show where Irina Rish may publish in the future.
Co-authors
The 25 scholars most cited alongside Irina Rish, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 85 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | An empirical study of the naive Bayes classifier Hit paper breakdown → | 2001 | 1698 |
| 2 | 2003 | 205 | |
| 3 | 2005 | 155 | |
| 4 | 2008 | 119 | |
| 5 | 2005 | 111 | |
| 6 | 2020 | 111 | |
| 7 | 2014 | 110 | |
| 8 | 2022 | 99 | |
| 9 | 2003 | 96 | |
| 10 | 2004 | 65 | |
| 11 | 2000 | 58 | |
| 12 | 2012 | 45 | |
| 13 | Recognizing End-User Transactions in Performance Management | 2000 | 35 |
| 14 | 2002 | 34 | |
| 15 | Mini-buckets: a general scheme for approximating inference | 2002 | 34 |
| 16 | 2022 | 31 | |
| 17 | 2008 | 28 | |
| 18 | Active probing strategies for problem diagnosis in distributed systems | 2003 | 25 |
| 19 | 2013 | 24 | |
| 20 | Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning | 2020 | 23 |
About Irina Rish
Irina Rish is a scholar working on Artificial Intelligence, Computer Networks and Communications, Cognitive Neuroscience, Molecular Biology and Management Science and Operations Research, having authored 85 papers that have together received 3.5k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (20 papers), Functional Brain Connectivity Studies (12 papers), Machine Learning and Algorithms (11 papers), Software System Performance and Reliability (9 papers), Neural dynamics and brain function (7 papers), Data Stream Mining Techniques (7 papers), Sparse and Compressive Sensing Techniques (6 papers) and Neural Networks and Applications (6 papers). The work is most often cited by research in Software (185 citations), Artificial Intelligence (1.5k citations), Computer Networks and Communications (904 citations), Signal Processing (352 citations) and Health Information Management (117 citations). Irina Rish has collaborated with scholars based in United States, Canada and France. Frequent co-authors include Rina Dechter, Genady Ya. Grabarnik, Alina Beygelzimer, Guillermo Cecchi, S. Ma, G. Grinstein, Ralph Linsker, Marc Brodie, Djallel Bouneffouf and Charų C. Aggarwal. Their work appears in journals such as IBM Journal of Research and Development, PLoS ONE, Scientific Reports, Journal of Vision and Schizophrenia.
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.