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cs.LG2026
Differentiable Interval Bottlenecks for Interpretable Anomaly Detection in Numerical Data
Lamine Diop, Marc Plantevit
Reconstruction-based anomaly detectors are accurate but opaque: a deep autoencoder flags a sample without telling a practitioner which feature ranges made it anomalous. We propose…
cs.LG2025
SEANN: A Domain-Informed Neural Network for Epidemiological Insights
Jean-Baptiste Guimbaud, Marc Plantevit, Léa Maître +1
In epidemiology, traditional statistical methods such as logistic regression, linear regression, and other parametric models are commonly employed to investigate associations betwe…
cs.LG2024
RPS: A Generic Reservoir Patterns Sampler
Lamine Diop, Marc Plantevit, Arnaud Soulet
Efficient learning from streaming data is important for modern data analysis due to the continuous and rapid evolution of data streams. Despite significant advancements in stream p…