Niv Giladi
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- Advanced Neural Network Applications 1
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- Machine Learning and Data Classification 2
- Stochastic Gradient Optimization Techniques 1
- Neural Networks and Applications 1
- Adversarial Robustness in Machine Learning 1
- Anomaly Detection Techniques and Applications 1
- Domain Adaptation and Few-Shot Learning 1
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- Advanced Memory and Neural Computing 1
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceComputational Theory and Mathematics
- Journals
- Sensors (1 paper)Repository for Publications and Research Data (ETH Zurich) (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- IsraelSwitzerlandUnited States
In The Last Decade
Niv Giladi
3 papers receiving 156 citations
Peers
Comparison fields: 5 of 52
- Computer Vision and Pattern Recognition 73
- Artificial Intelligence 76
- Computational Theory and Mathematics 17
- Control and Systems Engineering 19
- Structural Biology 1
Countries citing papers authored by Niv Giladi
This map shows the geographic impact of Niv Giladi'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 Niv Giladi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Niv Giladi more than expected).
Fields of papers citing papers by Niv Giladi
This network shows the impact of papers produced by Niv Giladi. 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 Niv Giladi. The network helps show where Niv Giladi may publish in the future.
Co-authorship network
The 7 scholars most cited alongside Niv Giladi, 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 | 2022 | 71 | |
| 2 | At Stability's Edge: How to Adjust Hyperparameters to Preserve Minima Selection in Asynchronous Training of Neural Networks? | 2020 | 1 |
| 3 | 2020 | 90 |
About Niv Giladi
Niv Giladi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 3 papers that have together received 162 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (2 papers), Stochastic Gradient Optimization Techniques (1 paper), Neural Networks and Applications (1 paper), Adversarial Robustness in Machine Learning (1 paper), Advanced Neural Network Applications (1 paper), Anomaly Detection Techniques and Applications (1 paper), Domain Adaptation and Few-Shot Learning (1 paper) and Advanced Memory and Neural Computing (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (73 citations), Artificial Intelligence (76 citations) and Computational Theory and Mathematics (17 citations). Niv Giladi has collaborated with scholars based in Israel, Switzerland and United States. Frequent co-authors include Ethan Fetaya, Dan Levi, Daniel Soudry, Elad Hoffer, Torsten Hoefler, Tal Ben‐Nun and Itay Hubara. Their work appears in journals such as Sensors, Repository for Publications and Research Data (ETH Zurich) and arXiv (Cornell University).
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.