Youssef Mroueh
- Signal Processing top 5%
- Speech and Audio Processing 3
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- Multimodal Machine Learning Applications 3
- Generative Adversarial Networks and Image Synthesis 2
- Artificial Intelligence top 10%
- Domain Adaptation and Few-Shot Learning 5
- Neural Networks and Applications 4
- Machine Learning and Algorithms 2
- Adversarial Robustness in Machine Learning 2
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- Sparse and Compressive Sensing Techniques 3
- Co-authors
- Payel DasEtienne MarcheretVaibhava GoelInkit PadhiBrian BelgodereJerret RossVijil ChenthamarakshanRaphaël Pestourie
- Cited by
- Signal ProcessingComputational Theory and MathematicsComputer Vision and Pattern Recognition
- Journals
- Nature Machine Intelligence (2 papers)npj Computational Materials (1 paper)Journal of Artificial Intelligence Research (1 paper)
- Partner nations
- United StatesItalySwitzerland
In The Last Decade
Youssef Mroueh
25 papers receiving 552 citations
Hit Papers
Peers
Comparison fields: 5 of 112
- Signal Processing 119
- Computational Theory and Mathematics 149
- Computer Vision and Pattern Recognition 131
- Artificial Intelligence 173
- Health Informatics 5
Countries citing papers authored by Youssef Mroueh
This map shows the geographic impact of Youssef Mroueh'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 Youssef Mroueh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Youssef Mroueh more than expected).
Fields of papers citing papers by Youssef Mroueh
This network shows the impact of papers produced by Youssef Mroueh. 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 Youssef Mroueh. The network helps show where Youssef Mroueh may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Youssef Mroueh, 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 | 2025 | 3 | |
| 2 | 2024 | 4 | |
| 3 | 2024 | 3 | |
| 4 | 2023 | 3 | |
| 5 | 2022 | 25 | |
| 6 | Large-scale chemical language representations capture molecular structure and propertiesbreakdown → | 2022 | 227 |
| 7 | 2021 | 2 | |
| 8 | 2021 | 5 | |
| 9 | 2020 | 53 | |
| 10 | Improved Adversarial Image Captioning | 2019 | 1 |
| 11 | 2019 | 5 | |
| 12 | Improved Image Captioning with Adversarial Semantic Alignment. | 2018 | 6 |
| 13 | Generative Feature Matching Networks | 2018 | 3 |
| 14 | Fisher GAN | 2017 | 9 |
| 15 | 2017 | 15 | |
| 16 | 2015 | 149 | |
| 17 | 2015 | 23 | |
| 18 | 2015 | 3 | |
| 19 | Multiclass Learning with Simplex Coding | 2012 | 6 |
| 20 | Multi-Class Learning: Simplex Coding And Relaxation Error | 2011 | 0 |
About Youssef Mroueh
Youssef Mroueh is a scholar working on Structural Biology, Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing and Statistical and Nonlinear Physics, having authored 27 papers that have together received 579 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (5 papers), Neural Networks and Applications (4 papers), Sparse and Compressive Sensing Techniques (3 papers), Speech and Audio Processing (3 papers), Multimodal Machine Learning Applications (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Machine Learning and Algorithms (2 papers) and Adversarial Robustness in Machine Learning (2 papers). The work is most often cited by research in Signal Processing (119 citations), Computational Theory and Mathematics (149 citations), Computer Vision and Pattern Recognition (131 citations), Artificial Intelligence (173 citations) and Health Informatics (5 citations). Youssef Mroueh has collaborated with scholars based in United States, Italy and Switzerland. Frequent co-authors include Payel Das, Etienne Marcheret, Vaibhava Goel, Inkit Padhi, Brian Belgodere, Jerret Ross, Vijil Chenthamarakshan, Raphaël Pestourie, Steven G. Johnson and Lorenzo Rosasco. Their work appears in journals such as Nature Machine Intelligence, npj Computational Materials, Journal of Artificial Intelligence Research, The Annals of Statistics and Foundations of Computational Mathematics.
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.