Pascal Germain
Impact in
- Artificial Intelligence top 10%
- Machine Learning and Algorithms
- Domain Adaptation and Few-Shot Learning
- Machine Learning and Data Classification
- Machine Learning and ELM
- Gaussian Processes and Bayesian Inference
- Imbalanced Data Classification Techniques
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- Medical Image Segmentation Techniques
- Face and Expression Recognition
Papers in
-
- Machine Learning and Algorithms 7
- Machine Learning and Data Classification 5
- Domain Adaptation and Few-Shot Learning 4
- Imbalanced Data Classification Techniques 3
- Neural Networks and Applications 3
- Gaussian Processes and Bayesian Inference 3
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- Face and Expression Recognition 3
- Co-authors
- François Laviolette (7 shared papers)Mario Marchand (6 shared papers)Nicolas Passat (1 shared paper)Christian Ronse (1 shared paper)J. Baruthio (1 shared paper)Hugo Larochelle (1 shared paper)Yaroslav Ganin (1 shared paper)Victor Lempitsky (1 shared paper)
In The Last Decade
Pascal Germain
18 papers receiving 249 citations
Peers
Comparison fields: 5 of 69
- Artificial Intelligence 168
- Computer Vision and Pattern Recognition 68
- Statistics and Probability 16
- Computational Mathematics 1
- Radiology, Nuclear Medicine and Imaging 30
Countries citing papers authored by Pascal Germain
This map shows the geographic impact of Pascal Germain'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 Germain with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pascal Germain more than expected).
Fields of papers citing papers by Pascal Germain
This network shows the impact of papers produced by Pascal Germain. 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 Germain. The network helps show where Pascal Germain may publish in the future.
Co-authors
The 25 scholars most cited alongside Pascal Germain, 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 | 2009 | 78 | |
| 2 | 2015 | 42 | |
| 3 | 2015 | 40 | |
| 4 | 2010 | 38 | |
| 5 | 2006 | 13 | |
| 6 | 2019 | 10 | |
| 7 | {PAC-Bayesian Theory for Transductive Learning} | 2014 | 8 |
| 8 | A PAC-Bayes Sample-compression Approach to Kernel Methods | 2011 | 8 |
| 9 | 2024 | 7 | |
| 10 | From PAC-Bayes Bounds to KL Regularization | 2009 | 7 |
| 11 | 2018 | 5 | |
| 12 | 2020 | 2 | |
| 13 | 2022 | 2 | |
| 14 | 2023 | 1 | |
| 15 | PAC-Bayesian Theorems for Domain Adaptation with Specialization to Linear Classifiers PAC-Bayesian Theorems for Multiview Learning | 2015 | 1 |
| 16 | 2022 | 1 | |
| 17 | 2024 | 1 | |
| 18 | A PAC-Bayes Sample-compression Approach to Kernel Methods : Supplementary material | 2011 | 1 |
| 19 | 2025 | 0 | |
| 20 | 2024 | 0 |
About Pascal Germain
Pascal Germain is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Molecular Biology and Computer Networks and Communications, having authored 20 papers that have together received 265 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (7 papers), Machine Learning and Data Classification (5 papers), Domain Adaptation and Few-Shot Learning (4 papers), Face and Expression Recognition (3 papers), Imbalanced Data Classification Techniques (3 papers), Neural Networks and Applications (3 papers), Fault Detection and Control Systems (3 papers) and Gaussian Processes and Bayesian Inference (3 papers). The work is most often cited by research in Artificial Intelligence (168 citations), Computer Vision and Pattern Recognition (68 citations), Statistics and Probability (16 citations), Computational Mathematics (1 citation) and Radiology, Nuclear Medicine and Imaging (30 citations). Pascal Germain has collaborated with scholars based in Canada, France and Russia. Frequent co-authors include François Laviolette, Mario Marchand, Nicolas Passat, Christian Ronse, J. Baruthio, Hugo Larochelle, Yaroslav Ganin, Victor Lempitsky, Evgeniya Ustinova and Emilie Morvant. Their work appears in journals such as Neurocomputing, Separation and Purification Technology, Computerized Medical Imaging and Graphics, Machine Learning and Analytical Chemistry.
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.