Ethan Perez
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- Multimodal Machine Learning Applications 6
- Advanced Image and Video Retrieval Techniques 2
- Artificial Intelligence top 2%
- Topic Modeling 7
- Natural Language Processing Techniques 4
- Domain Adaptation and Few-Shot Learning 2
- Neural Networks and Applications 1
- Signal Processing top 5%
- Health Informatics top 10%
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- Fluid Dynamics and Turbulent Flows 1
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- Turbomachinery Performance and Optimization 1
- Co-authors
- Aaron CourvilleVincent DumoulinFlorian StrubHarm de VriesSaffron HuangFrancis SongGeoffrey IrvingJohn Aslanides
- Journals
- HAL (Le Centre pour la Communication Scientifique Directe) (2 papers)Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- United StatesIsraelCanada
In The Last Decade
Ethan Perez
12 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Computer Vision and Pattern Recognition 566
- Artificial Intelligence 596
- Signal Processing 163
- Health Informatics 20
- Computer Graphics and Computer-Aided Design 29
Countries citing papers authored by Ethan Perez
This map shows the geographic impact of Ethan Perez'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 Ethan Perez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ethan Perez more than expected).
Fields of papers citing papers by Ethan Perez
This network shows the impact of papers produced by Ethan Perez. 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 Ethan Perez. The network helps show where Ethan Perez may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ethan Perez, 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 | 2023 | 1 | |
| 2 | 2022 | 3 | |
| 3 | 2022 | 128 | |
| 4 | 2022 | 2 | |
| 5 | 2022 | 1 | |
| 6 | True Few-Shot Learning with Language Models | 2021 | 5 |
| 7 | 2021 | 71 | |
| 8 | Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks | 2020 | 2 |
| 9 | 2019 | 8 | |
| 10 | HoME: a Household Multimodal Environment. | 2018 | 3 |
| 11 | 2018 | 78 | |
| 12 | FiLM: Visual Reasoning with a General Conditioning Layerbreakdown → | 2018 | 788 |
About Ethan Perez
Ethan Perez is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mechanics, Information Systems and Aerospace Engineering, having authored 12 papers that have together received 1.1k indexed citations. Recurring topics across this work include Topic Modeling (7 papers), Multimodal Machine Learning Applications (6 papers), Natural Language Processing Techniques (4 papers), Advanced Image and Video Retrieval Techniques (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Fluid Dynamics and Turbulent Flows (1 paper), Neural Networks and Applications (1 paper) and Turbomachinery Performance and Optimization (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (566 citations), Artificial Intelligence (596 citations), Signal Processing (163 citations), Health Informatics (20 citations) and Computer Graphics and Computer-Aided Design (29 citations). Ethan Perez has collaborated with scholars based in United States, Israel and Canada. Frequent co-authors include Aaron Courville, Vincent Dumoulin, Florian Strub, Harm de Vries, Saffron Huang, Francis Song, Geoffrey Irving, John Aslanides, Amelia Glaese and Trevor Cai. Their work appears in journals such as HAL (Le Centre pour la Communication Scientifique Directe), Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings of the AAAI Conference on Artificial Intelligence, Neural Information Processing Systems and UCL Discovery (University College London).
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.