The Shape of a Point Set in Three Dimensional Space. - Liang Chen; Mahmoud Melkemi; Laurent Meunier; Denis Vandorpe (Computer Graphics and Imaging, 2003)

Theoretical evidence for adversarial robustness through randomization. - Rafael Pinot; Laurent Meunier; Alexandre Araujo; Hisashi Kashima; Florian Yger; Cédric Gouy-Pailler; Jamal Atif (NeurIPS, 2019)

Theoretical evidence for adversarial robustness through randomization: the case of the Exponential family. - Rafael Pinot; Laurent Meunier; Alexandre Araujo; Hisashi Kashima; Florian Yger; Cédric Gouy-Pailler; Jamal Atif (CoRR, 2019)

Robust Neural Networks using Randomized Adversarial Training. - Alexandre Araujo; Rafael Pinot; Benjamin Négrevergne; Laurent Meunier; Yann Chevaleyre; Florian Yger; Jamal Atif (CoRR, 2019)

Yet another but more efficient black-box adversarial attack: tiling and evolution strategies. - Laurent Meunier; Jamal Atif; Olivier Teytaud (CoRR, 2019)

Adversarial Attacks on Linear Contextual Bandits. - Evrard Garcelon; Baptiste Rozière; Laurent Meunier; Jean Tarbouriech; Olivier Teytaud; Alessandro Lazaric; Matteo Pirotta (NeurIPS, 2020)

Advocating for Multiple Defense Strategies Against Adversarial Examples. - Alexandre Araujo; Laurent Meunier; Rafael Pinot; Benjamin Négrevergne (PKDD/ECML Workshops, 2020)

On Averaging the Best Samples in Evolutionary Computation. - Laurent Meunier; Yann Chevaleyre; Jérémy Rapin; Clément W. Royer; Olivier Teytaud (PPSN (2), 2020)

Variance Reduction for Better Sampling in Continuous Domains. - Laurent Meunier; Carola Doerr; Jérémy Rapin; Olivier Teytaud (PPSN (1), 2020)

Proving μ>1. - Laurent Meunier; Yann Chevaleyre; Jérémy Rapin; Clément W. Royer; Olivier Teytaud (CoRR, 2020)

Handling Multiple Costs in Optimal Transport: Strong Duality and Efficient Computation. - Meyer Scetbon; Laurent Meunier; Jamal Atif; Marco Cuturi (CoRR, 2020)

Equitable and Optimal Transport with Multiple Agents. - Meyer Scetbon; Laurent Meunier; Jamal Atif; Marco Cuturi (AISTATS, 2021)

Asymptotic convergence rates for averaging strategies. - Laurent Meunier; Iskander Legheraba; Yann Chevaleyre; Olivier Teytaud (FOGA, 2021)

Mixed Nash Equilibria in the Adversarial Examples Game. - Laurent Meunier; Meyer Scetbon; Rafael Pinot; Jamal Atif; Yann Chevaleyre (ICML, 2021)

ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients. - Alessandro Cappelli; Julien Launay; Laurent Meunier; Ruben Ohana; Iacopo Poli (CoRR, 2021)

Scalable Lipschitz Residual Networks with Convex Potential Flows. - Laurent Meunier; Blaise Delattre; Alexandre Araujo; Alexandre Allauzen (CoRR, 2021)

An 𝓁p-based Kernel Conditional Independence Test. - Meyer Scetbon; Laurent Meunier; Yaniv Romano (CoRR, 2021)

Adversarial Robustness by Design Through Analog Computing And Synthetic Gradients. - Alessandro Cappelli; Ruben Ohana; Julien Launay; Laurent Meunier; Iacopo Poli; Florent Krzakala (ICASSP, 2022)

A Dynamical System Perspective for Lipschitz Neural Networks. - Laurent Meunier; Blaise Delattre; Alexandre Araujo; Alexandre Allauzen (ICML, 2022)

An Asymptotic Test for Conditional Independence using Analytic Kernel Embeddings. - Meyer Scetbon; Laurent Meunier; Yaniv Romano (ICML, 2022)

Towards Consistency in Adversarial Classification. - Laurent Meunier; Raphael Ettedgui; Rafael Pinot; Yann Chevaleyre; Jamal Atif (NeurIPS, 2022)

On the robustness of randomized classifiers to adversarial examples. - Rafael Pinot; Laurent Meunier; Florian Yger; Cédric Gouy-Pailler; Yann Chevaleyre; Jamal Atif (Mach. Learn., 2022)

Black-Box Optimization Revisited: Improving Algorithm Selection Wizards Through Massive Benchmarking. - Laurent Meunier; Herilalaina Rakotoarison; Pak-Kan Wong; Baptiste Rozière; Jérémy Rapin; Olivier Teytaud; Antoine Moreau; Carola Doerr (IEEE Trans. Evol. Comput., 2022)

Adversarial attacks: a theoretical journey. (Attaques adverses: un point de vue théorique). - Laurent Meunier (2022)

On the Role of Randomization in Adversarially Robust Classification. - Lucas Gnecco Heredia; Muni Sreenivas Pydi; Laurent Meunier; Benjamin Négrevergne; Yann Chevaleyre (NeurIPS, 2023)

Randomization for adversarial robustness: the Good, the Bad and the Ugly. - Lucas Gnecco Heredia; Yann Chevaleyre; Benjamin Négrevergne; Laurent Meunier (CoRR, 2023)