Florian Strub
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- Multimodal Machine Learning Applications 7
- Advanced Image and Video Retrieval Techniques 3
- Signal Processing top 5%
- Artificial Intelligence top 5%
- Domain Adaptation and Few-Shot Learning 3
- Topic Modeling 3
- Speech and dialogue systems 2
- Reinforcement Learning in Robotics 2
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- Welding Techniques and Residual Stresses 1
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- Scheduling and Optimization Algorithms 1
- Co-authors
- Aaron CourvilleHarm de VriesVincent DumoulinEthan PerezTresa M. PollockMarie‐Agathe CharpagneNathan SchucherYoshua Bengio
- Journals
- Materials Characterization (1 paper)Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (1 paper)SPIRE - Sciences Po Institutional REpository (1 paper)
- Partner nations
- United StatesCanadaFrance
In The Last Decade
Florian Strub
10 papers receiving 936 citations
Hit Papers
Peers
Comparison fields: 5 of 95
- Computer Vision and Pattern Recognition 574
- Signal Processing 155
- Artificial Intelligence 451
- Computer Graphics and Computer-Aided Design 30
- Structural Biology 6
Countries citing papers authored by Florian Strub
This map shows the geographic impact of Florian Strub'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 Florian Strub with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Florian Strub more than expected).
Fields of papers citing papers by Florian Strub
This network shows the impact of papers produced by Florian Strub. 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 Florian Strub. The network helps show where Florian Strub may publish in the future.
Co-authorship network
The 21 scholars most cited alongside Florian Strub, 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 | 2024 | 2 | |
| 2 | 2022 | 2 | |
| 3 | 2020 | 2 | |
| 4 | 2020 | 2 | |
| 5 | 2019 | 40 | |
| 6 | HoME: a Household Multimodal Environment. | 2018 | 3 |
| 7 | 2018 | 78 | |
| 8 | FiLM: Visual Reasoning with a General Conditioning Layerbreakdown → | 2018 | 788 |
| 9 | Modulating early visual processing by language | 2017 | 11 |
| 10 | 2017 | 36 |
About Florian Strub
Florian Strub is a scholar working on Metals and Alloys, Computer Vision and Pattern Recognition, Artificial Intelligence, Industrial and Manufacturing Engineering and Mechanical Engineering, having authored 10 papers that have together received 964 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (7 papers), Advanced Image and Video Retrieval Techniques (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Topic Modeling (3 papers), Speech and dialogue systems (2 papers), Reinforcement Learning in Robotics (2 papers), Welding Techniques and Residual Stresses (1 paper) and Scheduling and Optimization Algorithms (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (574 citations), Signal Processing (155 citations), Artificial Intelligence (451 citations), Computer Graphics and Computer-Aided Design (30 citations) and Structural Biology (6 citations). Florian Strub has collaborated with scholars based in United States, Canada and France. Frequent co-authors include Aaron Courville, Harm de Vries, Vincent Dumoulin, Ethan Perez, Tresa M. Pollock, Marie‐Agathe Charpagne, Nathan Schucher, Yoshua Bengio, Olivier Pietquin and Bilal Piot. Their work appears in journals such as Materials Characterization, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, SPIRE - Sciences Po Institutional REpository, LillOA (Université de Lille (University Of Lille)) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.