Jean-Philippe Ovarlez — accepted AI-conference papers

2026

GEPC: Group-Equivariant Posterior Consistency for Out-of-Distribution Detection in Diffusion Models

Rouzoumka Yadang Alexis, Jean Pinsolle, Eugénie TERREAUX, christele morisseau, Jean-Philippe Ovarlez, Chengfang Ren

ICML 2026poster

Diffusion models learn a time-indexed score field $\mathbf{s}_\theta(\mathbf{x}_t,t)$ that often inherits approximate equivariances (flips, rotations, circular shifts) from in-distribution (ID) data and convolutional backbones. Most diffusion-based out-of-distribution (OOD) detectors exploit score m…

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2026

LATENT-SPACE METRICS FOR COMPLEX-VALUED VAE OUT-OF-DISTRIBUTION DETECTION UNDER RADAR CLUTTER

Yadang Alexis Rouzoumka, Eugénie Terreaux, Jean-Philippe Ovarlez, Chengfang Ren

ICASSP 2026poster

We investigate complex-valued Variational AutoEncoders (CVAE) for radar Out-Of-Distribution (OOD) detection in complex radar environments. We proposed several detection metrics: the reconstruction error of CVAE (CVAE-MSE), the latent-based scores (Mahalanobis, Kullback-Leibler divergence (KLD)), and…

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2026

SUPPORT VECTOR DATA DESCRIPTION FOR RADAR TARGET DETECTION

Jean PINSOLLE, Yadang Alexis Rouzoumka, Chengfang Ren, Christèle Morisseau, Jean-Philippe Ovarlez

ICASSP 2026poster

Classical radar detection techniques rely on adaptive detectors that estimate the noise covariance matrix from target-free secondary data. While effective in Gaussian environments, these methods degrade in the presence of clutter, which is better modeled by heavy-tailed distributions such as the Com…

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