Irina Rish

7.7k total citations · 1 hit paper
84 papers, 3.5k citations indexed

About

Irina Rish is a scholar working on Artificial Intelligence, Computer Networks and Communications and Cognitive Neuroscience. According to data from OpenAlex, Irina Rish has authored 84 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Artificial Intelligence, 22 papers in Computer Networks and Communications and 17 papers in Cognitive Neuroscience. Recurrent topics in Irina Rish's work include Bayesian Modeling and Causal Inference (20 papers), Functional Brain Connectivity Studies (12 papers) and Machine Learning and Algorithms (11 papers). Irina Rish is often cited by papers focused on Bayesian Modeling and Causal Inference (20 papers), Functional Brain Connectivity Studies (12 papers) and Machine Learning and Algorithms (11 papers). Irina Rish collaborates with scholars based in United States, Canada and France. Irina Rish's co-authors include Rina Dechter, Genady Ya. Grabarnik, Alina Beygelzimer, Guillermo Cecchi, S. Ma, Ralph Linsker, G. Grinstein, Marc Brodie, Djallel Bouneffouf and Charų C. Aggarwal and has published in prestigious journals such as PLoS ONE, NeuroImage and Scientific Reports.

In The Last Decade

Irina Rish

79 papers receiving 3.2k citations

Hit Papers

An empirical study of the naive Bayes classifier 2001 2026 2009 2017 2001 500 1000 1.5k

Peers

Irina Rish
Comparison fields: 5 of 191
  • Artificial Intelligence 1.5k
  • Computer Networks and Communications 899
  • Information Systems 611
  • Computer Vision and Pattern Recognition 399
  • Signal Processing 351
Replace Edwin V. Bonilla with:
Edwin V. Bonilla Australia
Randall Wald United States
Ramón Sangüesa Spain
Geoffrey J. Gordon United States
Ganqu Cui China
Gautam Biswas United States
Marc K. Albert United States
Zhengyan Zhang China
Hao Peng China
Charles X. Ling Canada
Edwin V. Bonilla Australia View profile →
Citations per field, relative to Irina Rish
Irina Rish · 1×
Citations per year, relative to Irina Rish
Irina Rish · 1×

Countries citing papers authored by Irina Rish

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Irina Rish

This figure shows the co-authorship network connecting the top 25 collaborators of Irina Rish. A scholar is included among the top collaborators of Irina Rish 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 Irina Rish. Irina Rish is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 1
3 3
4 9
5 28
6
Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning
23
7
Beyond Backprop: Alternating Minimization with co-Activation Memory.
4
8 5
9 24
10
Variable Selection for Gaussian Graphical Models
8
11
Sparse Markov Net Learning with Priors on Regularization Parameters
2
12
Active Collaborative Prediction with Maximum Margin Matrix Factorization.
11
13 111
14
Active probing strategies for problem diagnosis in distributed systems
25
15
Approximability of Probability Distributions
7
16 23
17
Inference Complexity as a Model-Selection Criterion for Learning Bayesian Networks.
2
18
Recognizing End-User Transactions in Performance Management
35
19
Approximation Algorithms for Probabilistic Decoding
1
20
Summarizing CSP hardness with continuous probability distributions
21

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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