Emmanuel Bengio
Impact in
- Artificial Intelligence top 5%
- Machine Learning and Data Classification
- Domain Adaptation and Few-Shot Learning
- Topic Modeling
- Machine Learning and Algorithms
- Anomaly Detection Techniques and Applications
- Adversarial Robustness in Machine Learning
- Natural Language Processing Techniques
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- Advanced Neural Network Applications
Papers in
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- Stochastic Gradient Optimization Techniques 2
- Privacy-Preserving Technologies in Data 1
- Text Readability and Simplification 1
- Advanced Graph Neural Networks 1
- Natural Language Processing Techniques 1
- Adversarial Robustness in Machine Learning 1
- Topic Modeling 1
- Neural Networks and Applications 1
- Co-authors
- Stanisław Jastrzȩbski (2 shared papers)Nicolas Ballas (2 shared papers)David Krueger (2 shared papers)Maxinder S Kanwal (2 shared papers)Tegan Maharaj (2 shared papers)Aaron Courville (2 shared papers)Devansh Arpit (2 shared papers)Asja Fischer (2 shared papers)
- Journals
- Jagiellonian University Repository (Jagiellonian University) (1 paper)PolyPublie (École Polytechnique de Montréal) (1 paper)
- Partner nations
- CanadaGermanyUnited States
In The Last Decade
Emmanuel Bengio
4 papers receiving 373 citations
Emmanuel Bengio's Hit Papers
Peers
Comparison fields: 5 of 67
- Artificial Intelligence 305
- Computer Vision and Pattern Recognition 157
- Industrial and Manufacturing Engineering 20
- Signal Processing 17
- Health Informatics 2
Countries citing papers authored by Emmanuel Bengio
This map shows the geographic impact of Emmanuel Bengio'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 Emmanuel Bengio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emmanuel Bengio more than expected).
Fields of papers citing papers by Emmanuel Bengio
This network shows the impact of papers produced by Emmanuel Bengio. 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 Emmanuel Bengio. The network helps show where Emmanuel Bengio may publish in the future.
Co-authors
The 19 scholars most cited alongside Emmanuel Bengio, 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 | A closer look at memorization in deep networks Hit paper breakdown → | 2017 | 348 |
| 2 | Deep Nets Don't Learn via Memorization | 2017 | 23 |
| 3 | 2017 | 11 | |
| 4 | Interference and Generalization in Temporal Difference Learning | 2020 | 1 |
| 5 | 2024 | 0 |
About Emmanuel Bengio
Emmanuel Bengio is a scholar working on Artificial Intelligence, Infectious Diseases, Organic Chemistry, Surgery and Communication, having authored 5 papers that have together received 383 indexed citations. Recurring topics across this work include Stochastic Gradient Optimization Techniques (2 papers), Privacy-Preserving Technologies in Data (1 paper), Text Readability and Simplification (1 paper), Advanced Graph Neural Networks (1 paper), Natural Language Processing Techniques (1 paper), Adversarial Robustness in Machine Learning (1 paper), Topic Modeling (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Artificial Intelligence (305 citations), Computer Vision and Pattern Recognition (157 citations), Industrial and Manufacturing Engineering (20 citations), Signal Processing (17 citations) and Health Informatics (2 citations). Emmanuel Bengio has collaborated with scholars based in Canada, Germany and United States. Frequent co-authors include Stanisław Jastrzȩbski, Nicolas Ballas, David Krueger, Maxinder S Kanwal, Tegan Maharaj, Aaron Courville, Devansh Arpit, Asja Fischer, Yoshua Bengio and Simon Lacoste-Julien. Their work appears in journals such as Jagiellonian University Repository (Jagiellonian University) and PolyPublie (École Polytechnique de Montréal).
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.