Faculty profile
Pascal Germain
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Research
Latest papers
QMAP: a benchmark for standardized evaluation of antimicrobial peptide MIC and hemolytic activity regression.
Scientific reports · 2026 · senior author
On Selecting Robust Approaches for Learning Predictive Biomarkers in Metabolomics Data Sets.
Analytical chemistry · 2025
Latest funding
- $12,500
PAC-Bayesian transfer learning: theory and algorithms
NSERC · 2020 · Principal investigator
- $145,000
PAC-Bayesian transfer learning: theory and algorithms
NSERC · 2020 · Principal investigator
2 publications.
QMAP: a benchmark for standardized evaluation of antimicrobial peptide MIC and hemolytic activity regression.
Lavertu A, Corbeil J, Germain P
On Selecting Robust Approaches for Learning Predictive Biomarkers in Metabolomics Data Sets.
Godon T, Plante PL, Corbeil J, Germain P, Drouin A
PAC-Bayesian transfer learning: theory and algorithms
Principal investigators: Germain, Pascal
PAC-Bayesian transfer learning: theory and algorithms
Principal investigators: Germain, Pascal
Keywords: machine learning; statistical learning; transfer learning; representation learning; domain adaptation; neural networks; kernel methods; pac-bayesian theory
From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.
Frequent collaborators
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