Pascal Vincent
Impact in
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- Generative Adversarial Networks and Image Synthesis
- Face and Expression Recognition
- Advanced Image and Video Retrieval Techniques
- Artificial Intelligence top 0.05%
- Anomaly Detection Techniques and Applications
- Topic Modeling
- Domain Adaptation and Few-Shot Learning
- Neural Networks and Applications
Papers in
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- Neural Networks and Applications 14
- Domain Adaptation and Few-Shot Learning 6
- Topic Modeling 6
- Machine Learning and Data Classification 5
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- Generative Adversarial Networks and Image Synthesis 15
- Face and Expression Recognition 6
- Co-authors
- Yoshua Bengio (32 shared papers)Pierre-Antoine Manzagol (3 shared papers)Hugo Larochelle (4 shared papers)Aaron Courville (7 shared papers)Dumitru Erhan (3 shared papers)Réjean Ducharme (3 shared papers)Salah Rifai (5 shared papers)Olivier Delalleau (5 shared papers)
- Journals
- Neural Computation (3 papers)Journal of Machine Learning Research (2 papers)Information and Inference A Journal of the IMA (1 paper)Machine Learning (1 paper)SAE technical papers on CD-ROM/SAE technical paper series (1 paper)
- Partner nations
- CanadaUnited StatesAlgeria
In The Last Decade
Pascal Vincent
48 papers receiving 13.1k citations
Pascal Vincent's Hit Papers
Peers
Comparison fields: 5 of 197
- Computer Vision and Pattern Recognition 5.6k
- Artificial Intelligence 6.8k
- Signal Processing 1.9k
- Media Technology 924
- Computational Mathematics 44
Countries citing papers authored by Pascal Vincent
This map shows the geographic impact of Pascal Vincent'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 Pascal Vincent with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pascal Vincent more than expected).
Fields of papers citing papers by Pascal Vincent
This network shows the impact of papers produced by Pascal Vincent. 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 Pascal Vincent. The network helps show where Pascal Vincent may publish in the future.
Co-authors
The 25 scholars most cited alongside Pascal Vincent, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Extracting and composing robust features with denoising autoencoders Hit paper breakdown → | 2008 | 4425 |
| 2 | Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion Hit paper breakdown → | 2010 | 3317 |
| 3 | Why Does Unsupervised Pre-training Help Deep Learning? Hit paper breakdown → | 2010 | 1372 |
| 4 | A Neural Probabilistic Language Model Hit paper breakdown → | 2000 | 678 |
| 5 | Contractive Auto-Encoders: Explicit Invariance During Feature Extraction Hit paper breakdown → | 2011 | 675 |
| 6 | Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering Hit paper breakdown → | 2003 | 599 |
| 7 | A Connection Between Score Matching and Denoising Autoencoders Hit paper breakdown → | 2011 | 477 |
| 8 | Unsupervised Feature Learning and Deep Learning: A Review and New Perspectives | 2012 | 274 |
| 9 | 2015 | 263 | |
| 10 | The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training | 2009 | 226 |
| 11 | 2004 | 205 | |
| 12 | 2002 | 189 | |
| 13 | K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms | 2001 | 126 |
| 14 | 2013 | 103 | |
| 15 | Unsupervised and Transfer Learning Challenge: a Deep Learning Approach | 2011 | 90 |
| 16 | The Manifold Tangent Classifier | 2011 | 87 |
| 17 | 2013 | 71 | |
| 18 | 2019 | 59 | |
| 19 | Convex Neural Networks | 2005 | 58 |
| 20 | Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines | 2010 | 54 |
About Pascal Vincent
Pascal Vincent is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Signal Processing and Computational Mechanics, having authored 48 papers that have together received 13.8k indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (15 papers), Neural Networks and Applications (14 papers), Model Reduction and Neural Networks (8 papers), Face and Expression Recognition (6 papers), Domain Adaptation and Few-Shot Learning (6 papers), Topic Modeling (6 papers), Machine Learning and Data Classification (5 papers) and Music and Audio Processing (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (5.6k citations), Artificial Intelligence (6.8k citations), Signal Processing (1.9k citations), Media Technology (924 citations) and Computational Mathematics (44 citations). Pascal Vincent has collaborated with scholars based in Canada, United States and Algeria. Frequent co-authors include Yoshua Bengio, Pierre-Antoine Manzagol, Hugo Larochelle, Aaron Courville, Dumitru Erhan, Réjean Ducharme, Salah Rifai, Olivier Delalleau, Xavier Muller and Nicolas Le Roux. Their work appears in journals such as Neural Computation, Journal of Machine Learning Research, Information and Inference A Journal of the IMA, Machine Learning and SAE technical papers on CD-ROM/SAE technical paper series.
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.