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cs.LG2026
Mitigating the reconstruction-detection trade-off in VAE-based unsupervised anomaly detection
Agathe Senellart, Maëlys Solal, Stéphanie Allassonnière +1
Variational autoencoders are widely used for unsupervised anomaly detection. Model selection however remains an open-question: to remain fully unsupervised, hyperparameters are oft…
cs.LG2025
Bridging the inference gap in Mutimodal Variational Autoencoders
Agathe Senellart, Stéphanie Allassonnière
From medical diagnosis to autonomous vehicles, critical applications rely on the integration of multiple heterogeneous data modalities. Multimodal Variational Autoencoders offer ve…