output
20232026
most citedOn the Krein-Rutman theorem and beyond

2 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

10 papers

math.DS2026

Backward bifurcations in spatial replicator models:when invasion criteria fail to predict coexistence

Tomas Freire, Erida Gjini, Sten Madec

The replicator equation is a central framework for studying frequency--dependent selection in ecology and evolutionary game theory. In well-mixed populations, the long-term outcome…

cs.LG2026

LiST: Lipschitz Scaling Training for Robust and Calibrated Neural Networks

Arthur Chiron, Franck Mamalet, Thomas Massena +2

While accuracy, robustness, and calibration are all essential for reliable neural networks, they are often studied separately; developing models that satisfy all three simultaneous…

cs.CV2026

LipSSD: Lipschitz-Constrained Single-Shot Detection for Adversarially Robust Object Detection

Vincent Lébé, Yannick Prudent, Corentin Friedrich +3

Object detectors have many applications in safety-critical systems, but they are known to be sensitive to worst-case perturbations such as adversarial attacks, which limits their a…

cs.AI2026

From SGD to Muon: Adaptive Optimization via Schatten-p Norms

Thomas Massena, Corentin Friedrich, Mathieu Serrurier

Modern optimizers, like Muon, impose matrix-wise geometry constraints on their updates. These matrix-wise constraints can be unified under Linear Minimization Oracle (LMO) theory.…

q-bio.PE2026

Multi-strain SIS dynamics with coinfection under host population structure

Sten Madec, Nicola Cinardi, Erida Gjini

Coinfection phenomena are common in nature, yet there is a lack of analytical approaches for coinfection systems with a high number of circulating and interacting strains. In this…

cs.CV2025

Fast and Flexible Robustness Certificates for Semantic Segmentation

Thomas Massena, Corentin Friedrich, Franck Mamalet +1

Deep Neural Networks are vulnerable to small perturbations that can drastically alter their predictions for perceptually unchanged inputs. The literature on adversarially robust De…

math.DS2025

Derivation of a spatial replicator system with environmental heterogeneity from a co-colonization SIS model with N strains and P patches

Sten Madec, Erida Gjini

The interplay between local and regional processes in the dynamics of ecological communities remains a challenge to model, analyze and predict. This is especially notable in infect…

cs.LG2025

Efficient Robust Conformal Prediction via Lipschitz-Bounded Networks

Thomas Massena, Léo andéol, Thibaut Boissin +4

Conformal Prediction (CP) has proven to be an effective post-hoc method for improving the trustworthiness of neural networks by providing prediction sets with finite-sample guarant…

stat.AP2025

Gaussian Process-driven Hidden Markov Models for Early Diagnosis of Infant Gait Anomalies

Luis Torres-Torres F., Jonatan Arias-García, Hernán F. García +2

Gait analysis is critical in the early detection and intervention of motor neurological disorders in infants. Despite its importance, traditional methods often struggle to model th…

math.AP2023★ 2 cited

On the Krein-Rutman theorem and beyond

Claudia Fonte Sanchez, Pierre Gabriel, Stéphane Mischler

In this work, we revisit the Krein-Rutman theory for semigroups of positive operators in a Banach lattice framework and we provide some very general, efficient and handy results wi…