Pascal Germain

8.7k total citations
19 papers, 259 citations indexed

About

Pascal Germain is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Pascal Germain has authored 19 papers receiving a total of 259 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 3 papers in Control and Systems Engineering. Recurrent topics in Pascal Germain's work include Machine Learning and Algorithms (7 papers), Machine Learning and Data Classification (5 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Pascal Germain is often cited by papers focused on Machine Learning and Algorithms (7 papers), Machine Learning and Data Classification (5 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Pascal Germain collaborates with scholars based in Canada, France and Russia. Pascal Germain's co-authors include François Laviolette, Mario Marchand, Nicolas Passat, Christian Ronse, J. Baruthio, Yaroslav Ganin, Evgeniya Ustinova, Hugo Larochelle, Victor Lempitsky and Emilie Morvant and has published in prestigious journals such as Analytical Chemistry, Separation and Purification Technology and Neurocomputing.

In The Last Decade

Pascal Germain

17 papers receiving 242 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Pascal Germain Canada	8	166	72	34	24	17	19	259
Renzhe Xu China	7	181 1.1×	105 1.5×	12 0.4×	18 0.8×	7 0.4×	17	276
Sebastian M. Schmon United Kingdom	5	130 0.8×	49 0.7×	32 0.9×	20 0.8×	15 0.9×	7	215
Sudhir Sawarkar India	9	115 0.7×	84 1.2×	9 0.3×	11 0.5×	18 1.1×	60	299
Aurélien Bibaut United States	4	107 0.6×	69 1.0×	59 1.7×	8 0.3×	14 0.8×	7	285
Sotiris K. Tasoulis Greece	10	102 0.6×	89 1.2×	15 0.4×	7 0.3×	40 2.4×	47	269
Xingxuan Zhang China	7	175 1.1×	108 1.5×	11 0.3×	17 0.7×	7 0.4×	12	263
Lifeng Wang China	9	62 0.4×	101 1.4×	14 0.4×	8 0.3×	8 0.5×	36	283
Harish G. Ramaswamy India	7	233 1.4×	131 1.8×	31 0.9×	4 0.2×	11 0.6×	14	321
Ilija Ilievski Singapore	6	143 0.9×	94 1.3×	19 0.6×	7 0.3×	9 0.5×	8	234
Hsin‐Hsiung Huang United States	9	42 0.3×	36 0.5×	17 0.5×	25 1.0×	18 1.1×	56	274

Countries citing papers authored by Pascal Germain

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Pascal Germain

This figure shows the co-authorship network connecting the top 25 collaborators of Pascal Germain. A scholar is included among the top collaborators of Pascal Germain based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pascal Germain. Pascal Germain is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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19 of 19 papers shown

Plante, Pier-Luc, et al.. (2025). On Selecting Robust Approaches for Learning Predictive Biomarkers in Metabolomics Data Sets. Analytical Chemistry. 97(24). 12669–12678.

Germain, Pascal, et al.. (2024). Application of machine learning tools to study the synergistic impact of physicochemical properties of peptides and filtration membranes on peptide migration during electrodialysis with filtration membranes. Separation and Purification Technology. 360. 130877–130877. 6 indexed citations

Germain, Pascal, et al.. (2024). Unsupervised Insider Threat Detection Using Multi-Head Self-Attention Mechanisms. 228–236.

Germain, Pascal, et al.. (2023). A general framework for the practical disintegration of PAC-Bayesian bounds. Machine Learning. 113(2). 519–604. 1 indexed citations

Zhang, Luxin, Pascal Germain, Yacine Kessaci, & Christophe Biernacki. (2022). Interpretable Domain Adaptation for Hidden Subdomain Alignment in the Context of Pre-trained Source Models. Proceedings of the AAAI Conference on Artificial Intelligence. 36(8). 9057–9065. 2 indexed citations

Zhang, Luxin, Pascal Germain, Yacine Kessaci, & Christophe Biernacki. (2022). Interpretable domain adaptation using unsupervised feature selection on pre-trained source models. Neurocomputing. 511. 319–336. 1 indexed citations

Esfahani, Alireza, et al.. (2020). Improved PAC-Bayesian Bounds for Linear Regression. Proceedings of the AAAI Conference on Artificial Intelligence. 34(4). 5660–5667. 2 indexed citations

Germain, Pascal, Amaury Habrard, François Laviolette, & Emilie Morvant. (2019). PAC-Bayes and domain adaptation. Neurocomputing. 379. 379–397. 10 indexed citations

Morvant, Emilie, et al.. (2018). Multiview Boosting by Controlling the Diversity and the Accuracy of View-specific Voters. arXiv (Cornell University). 5 indexed citations

10.

Germain, Pascal, Amaury Habrard, François Laviolette, & Emilie Morvant. (2015). PAC-Bayesian Theorems for Domain Adaptation with Specialization to Linear Classifiers PAC-Bayesian Theorems for Multiview Learning. arXiv (Cornell University). 1 indexed citations

11.

Ganin, Yaroslav, Evgeniya Ustinova, Pascal Germain, et al.. (2015). Domain-Adversarial Training of Neural Networks. arXiv (Cornell University). 42 indexed citations

12.

Germain, Pascal, et al.. (2015). Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm. arXiv (Cornell University). 16(1). 787–860. 38 indexed citations

13.

Germain, Pascal, et al.. (2014). {PAC-Bayesian Theory for Transductive Learning}. International Conference on Artificial Intelligence and Statistics. 105–113. 8 indexed citations

14.

Germain, Pascal, et al.. (2011). A PAC-Bayes Sample-compression Approach to Kernel Methods. International Conference on Machine Learning. 297–304. 8 indexed citations

15.

Germain, Pascal, et al.. (2011). A PAC-Bayes Sample-compression Approach to Kernel Methods : Supplementary material. 1 indexed citations

16.

Ronse, Christian, et al.. (2010). 3D segmentation of coronary arteries based on advanced mathematical morphology techniques. Computerized Medical Imaging and Graphics. 34(5). 377–387. 37 indexed citations

17.

Germain, Pascal, et al.. (2009). From PAC-Bayes Bounds to KL Regularization. Neural Information Processing Systems. 22. 603–610. 7 indexed citations

18.

Germain, Pascal, et al.. (2009). PAC-Bayesian learning of linear classifiers. 353–360. 77 indexed citations

19.

Germain, Pascal, et al.. (2006). La re-territorialisation du développement agricole : le cas de l'agriculture périurbaine d'Angers. Revue d’Économie Régionale & Urbaine. août(3). 373–392. 13 indexed citations

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.

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