Itay Hubara
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Electrical and Electronic Engineering
- Signal Processing
- Computer Networks and Communications
- Co-authors
- Daniel SoudryElad HofferRon MeirRon BannerNiv GiladiTorsten HoeflerTal Ben‐NunYury Nahshan
- Topics
- Advanced Neural Network Applications (5 papers)Neural Networks and Applications (4 papers)Domain Adaptation and Few-Shot Learning (3 papers)
- Journals
- Semiconductor Science and TechnologyVascular and Endovascular SurgeryRepository for Publications and Research Data (ETH Zurich)
- Partner nations
- IsraelUnited StatesSwitzerland
In The Last Decade
Itay Hubara
10 papers receiving 764 citations
Hit Papers
Peers
Comparison fields: 5 of 74
- Computer Vision and Pattern Recognition 515
- Artificial Intelligence 450
- Electrical and Electronic Engineering 226
- Signal Processing 42
- Computer Networks and Communications 41
Countries citing papers authored by Itay Hubara
This map shows the geographic impact of Itay Hubara'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 Itay Hubara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Itay Hubara more than expected).
Fields of papers citing papers by Itay Hubara
This network shows the impact of papers produced by Itay Hubara. 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 Itay Hubara. The network helps show where Itay Hubara may publish in the future.
Co-authorship network of co-authors of Itay Hubara
This figure shows the co-authorship network connecting the top 25 collaborators of Itay Hubara. A scholar is included among the top collaborators of Itay Hubara 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 Itay Hubara. Itay Hubara is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | Accurate Post Training Quantization With Small Calibration Sets | 20 |
| 3 | 8 | |
| 4 | 90 | |
| 5 | Scalable methods for 8-bit training of neural networks | 52 |
| 6 | Quantized Back-Propagation: Training Binarized Neural Networks with Quantized Gradients | 4 |
| 7 | Train longer, generalize better: closing the generalization gap in large batch training of neural networks | 48 |
| 8 | Binarized Neural Networksbreakdown → | 481 |
| 9 | 1 | |
| 10 | Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights | 86 |
About Itay Hubara
Itay Hubara is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Developmental and Educational Psychology, having authored 10 papers that have together received 791 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (5 papers), Neural Networks and Applications (4 papers) and Domain Adaptation and Few-Shot Learning (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (515 citations), Computational Mathematics (9 citations) and Artificial Intelligence (450 citations). Itay Hubara has collaborated with scholars based in Israel, United States and Switzerland. Frequent co-authors include Daniel Soudry, Elad Hoffer, Ron Meir, Ron Banner, Niv Giladi, Torsten Hoefler, Tal Ben‐Nun, Yury Nahshan, Yair Hanani and Besma Nejim. Their work appears in journals such as Semiconductor Science and Technology, Vascular and Endovascular Surgery and Repository for Publications and Research Data (ETH Zurich).
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.