collaborators

6 papers

cs.SD2026

Determinantal point process sampling for bioacoustic active learning

Hugo Magaldi, Gabriel Dubus

Eco-acoustic monitoring generates vast volumes of audio data, making active learning a promising approach for reducing annotation effort while efficiently training reliable biodive…

cs.SD2026

Adaptive Diversity-Uncertainty Active Learning with Redundancy Control for Bioacoustic Event Classification

Gabriel Dubus, Hugo Magaldi, Anatole Gros-Martial

Active learning is a promising framework for reducing annotation costs in large-scale bioacoustic monitoring, where expert labeling is expensive and data distributions are highly h…

cs.CV2026

DeepForestVisionV2: Ecology-Driven Taxonomy Expansion for Camera-Trap Monitoring in African Tropical Forests

Hugo Magaldi, Theau d'Audiffret, Etienne Francois Akomo-Okoue +24

Camera-trap monitoring in African tropical forests increasingly extends beyond closed-canopy interiors to riverbanks, clearings, and park edges. Among available open tools for Afri…

cs.SD2026

DeepForestSound: a multi-species automatic detector for passive acoustic monitoring in African tropical forests, a case study in Kibale National Park

Gabriel Dubus, Théau d'Audiffret, Claire Auger +10

Passive Acoustic Monitoring (PAM) is widely used for biodiversity assessment. Its application in African tropical forests is limited by scarce annotated data, reducing the performa…

math.PR2026

The spectrum of the stochastic Bessel operator at high temperature

Laure Dumaz, Hugo Magaldi

Ramírez and Rider (2009) established that the hard edge of the spectrum of the -Laguerre ensemble converges, in the high-dimensional limit, to the bottom of the spectrum of th…

math.PR2024

The stochastic Bessel operator at high temperatures

Hugo Magaldi

We know from Ram{í}rez and Rider that the hard edge of the spectrum of the Beta-Laguerre ensemble converges, in the high-dimensional limit, to the bottom of the spectrum of the st…