Pascal Vincent
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- Generative Adversarial Networks and Image Synthesis 15
- Face and Expression Recognition 6
- Artificial Intelligence top 0.05%
- Neural Networks and Applications 14
- Topic Modeling 6
- Domain Adaptation and Few-Shot Learning 6
- Machine Learning and Data Classification 5
- Signal Processing top 0.2%
- Media Technology top 0.2%
- Computational Mathematics top 2%
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- Model Reduction and Neural Networks 8
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- Sparse and Compressive Sensing Techniques 4
- Co-authors
- Yoshua BengioPierre-Antoine ManzagolHugo LarochelleAaron CourvilleDumitru ErhanRéjean DucharmeSalah RifaiOlivier Delalleau
- Journals
- Neural Computation (3 papers)Journal of Machine Learning Research (2 papers)Information and Inference A Journal of the IMA (1 paper)
- Partner nations
- CanadaUnited StatesAlgeria
In The Last Decade
Pascal Vincent
48 papers receiving 13.1k citations
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-authorship network
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
| # | Work | ||
|---|---|---|---|
| 1 | A Closer Look at the Optimization Landscapes of Generative Adversarial Networks | 2020 | 4 |
| 2 | Unreproducible Research is Reproducible | 2019 | 20 |
| 3 | Convergent Tree Backup and Retrace with Function Approximation | 2018 | 4 |
| 4 | A Variational Inequality Perspective on Generative Adversarial Networks | 2018 | 8 |
| 5 | Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis | 2018 | 9 |
| 6 | An Exploration of Softmax Alternatives Belonging to the Spherical Loss Family | 2016 | 11 |
| 7 | Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets. | 2015 | 8 |
| 8 | A Generative Process for Contractive Auto-Encoders. | 2012 | 3 |
| 9 | Contractive Auto-Encoders: Explicit Invariance During Feature Extractionbreakdown → | 2011 | 675 |
| 10 | The Manifold Tangent Classifier | 2011 | 87 |
| 11 | Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines | 2010 | 54 |
| 12 | Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterionbreakdown → | 2010 | 3317 |
| 13 | Why Does Unsupervised Pre-training Help Deep Learning?breakdown → | 2010 | 1372 |
| 14 | Deep Learning using Robust Interdependent Codes | 2009 | 17 |
| 15 | The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training | 2009 | 226 |
| 16 | Non-Local Manifold Parzen Windows | 2005 | 31 |
| 17 | Convex Neural Networks | 2005 | 58 |
| 18 | Manifold Parzen Windows | 2002 | 54 |
| 19 | Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference | 2001 | 12 |
| 20 | K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms | 2001 | 126 |
About Pascal Vincent
Pascal Vincent is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Health Informatics, 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), Topic Modeling (6 papers), Face and Expression Recognition (6 papers), Domain Adaptation and Few-Shot Learning (6 papers), Machine Learning and Data Classification (5 papers) and Sparse and Compressive Sensing Techniques (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (5.6k citations), Artificial Intelligence (6.8k citations) and Signal Processing (1.9k 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.