35 citations · 61 across the 11 of their papers we have counts for
12 papers
Transformer-based Diffusion models for Hydrological Time Series Probabilistic Imputation and Forecasting
Ferdinand Bhavsar, Lionel Benoit, Maxime Savatier +1
The modeling of hydrometeorological time series with limited observations is a key challenge in the monitoring of hydro-systems and water resources, as well as for flood or drought…
A spatio-temporal hybrid Strauss hardcore point process for forest fire occurrences
Morteza Raeisi, Florent Bonneu, Edith Gabriel
We propose a new point process model that combines, in the spatio-temporal setting, both multi-scaling by hybridization and hardcore distances. Our so-called hybrid Strauss hardcor…
Anti-Backdoor Learning: Training Clean Models on Poisoned Data
Yige Li, Xixiang Lyu, Nodens Koren +3
Backdoor attack has emerged as a major security threat to deep neural networks (DNNs). While existing defense methods have demonstrated promising results on detecting or erasing ba…
Mapping the intensity function of a non-stationary point process in unobserved areas
Edith Gabriel, Francisco J. Rodríguez-Cortes, Jérôme Coville +2
Seismic networks provide data that are used as basis both for public safety decisions and for scientific research. Their configuration affects the data completeness, which in turn,…
On spatial and spatio-temporal multi-structure point process models
Morteza Raeisi, Florent Bonneu, Edith Gabriel
Spatial and spatio-temporal single-structure point process models are widely used in epidemiology, biology, ecology, seismology... . However, most natural phenomena present multipl…
Landscape allocation: stochastic generators and statistical inference
Patrizia Zamberletti, Julien Papaïx, Edith Gabriel +1
In agricultural landscapes, the composition and spatial configuration of cultivated and semi-natural elements strongly impact species dynamics, their interactions and habitat conne…