Publications

You can also find my articles on my Google Scholar profile. To cite the papers, please use the citations here.

Articles

Valorization of turkey cruor through peptic hydrolysis: peptidomics and machine learning approaches for the identification of antimicrobial peptides

Houssine Fliss, Mathieu Bazinet, Sara García-Vela, Jacinthe Thibodeau, Laurent Bazinet, Sergey Mikhaylin

Food Chemistry, April 2026

Impact of hydrolysis duration and discoloration on peptide profiles and antimicrobial properties in chicken cruor hydrolysates: Identification of five novel antifungal peptides

Delasa Rahimi, Mathieu Bazinet, Zain Sanchez-Reinoso, Sara García-Vela, Juan de Toro-Martín, Sergey Mikaylin, Laurent Bazinet

Food Chemistry, March 2026

Identification of antihypertensive, antidiabetic, and antioxidant peptides derived from hydrolysates of dairy white wastewaters containing milk proteins using machine learning insights

Diala Damen, Hairati Aboubacar, Aurore Cournoyer, Mathieu Bazinet, Juan de Toro-Martín, Sami Gaaloul, Safia Hamoudi, Benoit Cudennec, Laurent Bazinet

Food Research International, January 2026

Generalization Bounds via Meta-Learned Model Representations: PAC-Bayes and Sample Compression Hypernetworks

Benjamin Leblanc, Mathieu Bazinet, Nathaniel D'Amours, Alexandre Drouin, Pascal Germain

ICML 2025

Long version of Sample Compression Hypernetworks: From Generalization Bounds to Meta-Learning

Sample Compression Unleashed: New Generalization Bounds for Real Valued Losses

Mathieu Bazinet, Valentina Zantedeschi, Pascal Germain

AISTATS 2025

Application of machine learning tools to study the synergistic impact of physicochemical properties.

Zain Sanchez-Reinoso, Mathieu Bazinet, Benjamin Leblanc, Jean-Pierre Clément, Pascal Germain, Laurent Bazinet

Separation and Purification Technology, December 2024

How peptide migration and fraction bioactivity are modulated by applied electrical current conditions during electromembrane process separation: A comprehensive machine learning-based peptidomic approach

Aurore Cournoyer, Mathieu Bazinet, Jean-Pierre Clément, Pier-Luc Plante, Ismail Fliss, Laurent Bazinet

Food Research International, November 2024

Preprints and submitted articles

Bound to Disagree : Generalization Bounds via Certifiable Surrogates

Mathieu Bazinet, Valentina Zantedeschi, Pascal Germain

Effects of Pulsed Electric Field Pulse/Pause Combination on Anionic Peptide Migration During Electromembrane Separation of a Whey Protein Hydrolysate: A Machine Learning-Based Comprehensive Study.

Leonel Cedrick Mafotang Tasgue, Mathieu Bazinet, Aurore Cournoyer, Marcello Fidaleo, Laurent Bazinet

Submitted to Food Research International.

Sample Compression for Self-Certified Continual Learning

Jacob Comeau*, Mathieu Bazinet*, Pascal Germain, Cem Subakan

* indicates equal contributions.

Wavelet-Based Feature Map for Kernel Approximation.

Mathieu Bazinet, Valentina Zantedeschi, Pascal Germain

This article was submitted at a conference in 2023, but was never published.

Workshop papers

Sample Compression Unleashed : New Generalization Bounds for Real Valued Losses.

Mathieu Bazinet, Valentina Zantedeschi, Pascal Germain

Workshop on Mathematics of Modern Machine Learning of NeurIPS 2024

Sample Compression Unleashed : New Generalization Bounds for Real Valued Losses.

Mathieu Bazinet, Valentina Zantedeschi, Pascal Germain

Workshop on Machine Learning and Compression of NeurIPS 2024

Sample Compression Hypernetworks: From Generalization Bounds to Meta-Learning.

Benjamin Leblanc, Mathieu Bazinet, Nathaniel D'Amours, Alexandre Drouin, Pascal Germain

Workshop on Machine Learning and Compression of NeurIPS 2024