Xavier Muller
Impact in
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- Generative Adversarial Networks and Image Synthesis
- Advanced Neural Network Applications
- Face and Expression Recognition
- Advanced Image and Video Retrieval Techniques
- Human Pose and Action Recognition
- Artificial Intelligence top 2%
- Anomaly Detection Techniques and Applications
- Domain Adaptation and Few-Shot Learning
- Neural Networks and Applications
Papers in
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- Generative Adversarial Networks and Image Synthesis 2
- Optical measurement and interference techniques 1
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- Machine Learning and Data Classification 2
- Neural Networks and Applications 2
- Domain Adaptation and Few-Shot Learning 2
- Machine Learning and Algorithms 1
- Co-authors
- Salah RifaiYoshua BengioPascal VincentXavier GlorotYann DauphinH. BürkhardtJames BergstraDavid Warde-Farley
- Journals
- IEEE Transactions on Acoustics Speech and Signal Processing (1 paper)Neural Information Processing Systems (1 paper)International Conference on Machine Learning (2 papers)
- Partner nations
- CanadaFranceUnited States
In The Last Decade
Xavier Muller
5 papers receiving 888 citations
Hit Papers
Peers
Comparison fields: 5 of 100
- Computer Vision and Pattern Recognition 465
- Artificial Intelligence 540
- Signal Processing 136
- Computational Mathematics 4
- Media Technology 48
Countries citing papers authored by Xavier Muller
This map shows the geographic impact of Xavier Muller'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 Xavier Muller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xavier Muller more than expected).
Fields of papers citing papers by Xavier Muller
This network shows the impact of papers produced by Xavier Muller. 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 Xavier Muller. The network helps show where Xavier Muller may publish in the future.
Co-authors
The 20 scholars most cited alongside Xavier Muller, 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 | Contractive Auto-Encoders: Explicit Invariance During Feature Extraction Hit paper breakdown → | 2011 | 675 |
| 2 | The Manifold Tangent Classifier | 2011 | 87 |
| 3 | Unsupervised and Transfer Learning Challenge: a Deep Learning Approach | 2011 | 90 |
| 4 | Deep Learners Benefit More from Out-of-Distribution Examples | 2011 | 52 |
| 5 | 1980 | 27 |
About Xavier Muller
Xavier Muller is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Statistical and Nonlinear Physics and Computational Theory and Mathematics, having authored 5 papers that have together received 931 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (2 papers), Neural Networks and Applications (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Topological and Geometric Data Analysis (1 paper), Digital Filter Design and Implementation (1 paper), Machine Learning and Algorithms (1 paper) and Optical measurement and interference techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (465 citations), Artificial Intelligence (540 citations), Signal Processing (136 citations), Computational Mathematics (4 citations) and Media Technology (48 citations). Xavier Muller has collaborated with scholars based in Canada, France and United States. Frequent co-authors include Salah Rifai, Yoshua Bengio, Pascal Vincent, Xavier Glorot, Yann Dauphin, H. Bürkhardt, James Bergstra, David Warde-Farley, Aaron Courville and Ian Goodfellow. Their work appears in journals such as IEEE Transactions on Acoustics Speech and Signal Processing, Neural Information Processing Systems and International Conference on Machine Learning.
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.