Gary Bécigneul
Impact in
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- Topic Modeling
- Natural Language Processing Techniques
- Advanced Graph Neural Networks
- Stochastic Gradient Optimization Techniques
- Domain Adaptation and Few-Shot Learning
Papers in
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- Natural Language Processing Techniques 2
- Speech Recognition and Synthesis 2
- Stochastic Gradient Optimization Techniques 2
- Sentiment Analysis and Opinion Mining 1
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- 3D Shape Modeling and Analysis 3
- Co-authors
- Octavian-Eugen Ganea (3 shared papers)Aurélien Lucchi (3 shared papers)Shiqi Yang (1 shared paper)Gregor Bachmann (1 shared paper)Sylvain Gelly (1 shared paper)Aliaksei Severyn (1 shared paper)
- Journals
- arXiv (Cornell University) (4 papers)International Conference on Artificial Intelligence and Statistics (2 papers)Repository for Publications and Research Data (ETH Zurich) (1 paper)
- Partner nations
- SwitzerlandUnited StatesChina
In The Last Decade
Gary Bécigneul
8 papers receiving 60 citations
Peers
Comparison fields: 5 of 27
- Computational Mathematics 1
- Artificial Intelligence 47
- Numerical Analysis 7
- Computer Vision and Pattern Recognition 22
- Computer Graphics and Computer-Aided Design 3
Countries citing papers authored by Gary Bécigneul
This map shows the geographic impact of Gary Bécigneul'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 Gary Bécigneul with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gary Bécigneul more than expected).
Fields of papers citing papers by Gary Bécigneul
This network shows the impact of papers produced by Gary Bécigneul. 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 Gary Bécigneul. The network helps show where Gary Bécigneul may publish in the future.
Co-authors
The 6 scholars most cited alongside Gary Bécigneul, 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 | Poincaré GloVe: Hyperbolic Word Embeddings | 2018 | 27 |
| 2 | Riemannian Adaptive Optimization Methods. | 2018 | 17 |
| 3 | Practical Accelerated Optimization on Riemannian Manifolds | 2020 | 5 |
| 4 | A Continuous-time Perspective for Modeling Acceleration in Riemannian Optimization. | 2020 | 4 |
| 5 | 2019 | 4 | |
| 6 | 2019 | 3 | |
| 7 | 2021 | 2 | |
| 8 | Momentum Improves Optimization on Riemannian Manifolds | 2021 | 1 |
About Gary Bécigneul
Gary Bécigneul is a scholar working on Artificial Intelligence, Computational Mechanics, Geometry and Topology, Social Psychology and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 63 indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (3 papers), Natural Language Processing Techniques (2 papers), Speech Recognition and Synthesis (2 papers), Stochastic Gradient Optimization Techniques (2 papers), Morphological variations and asymmetry (2 papers), Sentiment Analysis and Opinion Mining (1 paper), Mathematical Biology Tumor Growth (1 paper) and Graph Theory and Algorithms (1 paper). The work is most often cited by research in Computational Mathematics (1 citation), Artificial Intelligence (47 citations), Numerical Analysis (7 citations), Computer Vision and Pattern Recognition (22 citations) and Computer Graphics and Computer-Aided Design (3 citations). Gary Bécigneul has collaborated with scholars based in Switzerland, United States and China. Frequent co-authors include Octavian-Eugen Ganea, Aurélien Lucchi, Shiqi Yang, Gregor Bachmann, Sylvain Gelly and Aliaksei Severyn. Their work appears in journals such as arXiv (Cornell University), International Conference on Artificial Intelligence and Statistics 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.