Inmar E. Givoni
Impact in
- Artificial Intelligence top 10%
- Advanced Clustering Algorithms Research
- Text and Document Classification Technologies
- Topic Modeling
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- Advanced Image and Video Retrieval Techniques
- Face and Expression Recognition
Papers in
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- Bayesian Modeling and Causal Inference 3
- Advanced Clustering Algorithms Research 2
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- Error Correcting Code Techniques 3
- Co-authors
- Brendan J. Frey (9 shared papers)Daniel Tarlow (2 shared papers)Richard S. Zemel (2 shared papers)Rakesh Agrawal (2 shared papers)Ariel Fuxman (2 shared papers)Nevena Lazic (1 shared paper)Parham Aarabi (1 shared paper)Anitha Kannan (2 shared papers)
- Journals
- Neural Computation (2 papers)Behavioural Brain Research (1 paper)Uncertainty in Artificial Intelligence (1 paper)Digital Access to Scholarship at Harvard (DASH) (Harvard University) (1 paper)Knowledge Discovery and Data Mining (1 paper)
- Partner nations
- CanadaUnited StatesSpain
In The Last Decade
Inmar E. Givoni
11 papers receiving 312 citations
Peers
Comparison fields: 5 of 57
- Artificial Intelligence 196
- Computer Vision and Pattern Recognition 121
- Computational Mathematics 2
- Statistical and Nonlinear Physics 36
- Signal Processing 30
Countries citing papers authored by Inmar E. Givoni
This map shows the geographic impact of Inmar E. Givoni'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 Inmar E. Givoni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Inmar E. Givoni more than expected).
Fields of papers citing papers by Inmar E. Givoni
This network shows the impact of papers produced by Inmar E. Givoni. 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 Inmar E. Givoni. The network helps show where Inmar E. Givoni may publish in the future.
Co-authors
The 14 scholars most cited alongside Inmar E. Givoni, 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 | 2009 | 97 | |
| 2 | HOP-MAP: Efficient Message Passing with High Order Potentials | 2010 | 62 |
| 3 | 2009 | 52 | |
| 4 | 2011 | 49 | |
| 5 | Semi-Supervised Affinity Propagation with Instance-Level Constraints | 2009 | 38 |
| 6 | 2012 | 10 | |
| 7 | Graph cuts is a max-product algorithm | 2011 | 9 |
| 8 | 2012 | 5 | |
| 9 | 2009 | 4 | |
| 10 | Matching Unstructured Offers to Structured Product Descriptions | 2011 | 3 |
| 11 | Min-Max Propagation | 2017 | 2 |
| 12 | 2011 | 0 | |
| 13 | Factorgrams: A tool for visualizing multi-way associations in biological data | 2006 | 0 |
About Inmar E. Givoni
Inmar E. Givoni is a scholar working on Artificial Intelligence, Computer Networks and Communications, Molecular Biology, Computer Vision and Pattern Recognition and Information Systems, having authored 13 papers that have together received 331 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Error Correcting Code Techniques (3 papers), Web Data Mining and Analysis (2 papers), Advanced Clustering Algorithms Research (2 papers), Gene expression and cancer classification (2 papers), Data Quality and Management (2 papers) and Genomics and Phylogenetic Studies (2 papers). The work is most often cited by research in Artificial Intelligence (196 citations), Computer Vision and Pattern Recognition (121 citations), Computational Mathematics (2 citations), Statistical and Nonlinear Physics (36 citations) and Signal Processing (30 citations). Inmar E. Givoni has collaborated with scholars based in Canada, United States and Spain. Frequent co-authors include Brendan J. Frey, Daniel Tarlow, Richard S. Zemel, Rakesh Agrawal, Ariel Fuxman, Nevena Lazic, Parham Aarabi, Anitha Kannan, Francesc S. Beltran and Vicenç Quera. Their work appears in journals such as Neural Computation, Behavioural Brain Research, Uncertainty in Artificial Intelligence, Digital Access to Scholarship at Harvard (DASH) (Harvard University) and Knowledge Discovery and Data Mining.
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.