1 citations · 2 across the 5 of their papers we have counts for
5 papers
Heavy-Tailed Class-Conditional Priors for Long-Tailed Generative Modeling
Aymene Mohammed Bouayed, Samuel Deslauriers-Gauthier, Adrian Iaccovelli +1
Variational Autoencoders (VAEs) with global priors trained under an imbalanced empirical class distribution can lead to underrepresentation of tail classes in the latent space. Whi…
CNN Explainability with Multivector Tucker Saliency Maps for Self-Supervised Models
Aymene Mohammed Bouayed, Samuel Deslauriers-Gauthier, Adrian Iaccovelli +1
Interpreting the decisions of Convolutional Neural Networks (CNNs) is essential for understanding their behavior, yet explainability remains a significant challenge, particularly f…
Sampling From Autoencoders' Latent Space via Quantization And Probability Mass Function Concepts
Aymene Mohammed Bouayed, Adrian Iaccovelli, David Naccache
In this study, we focus on sampling from the latent space of generative models built upon autoencoders so as the reconstructed samples are lifelike images. To do to, we introduce a…
Simplex Autoencoders
Aymene Mohammed Bouayed, David Naccache
Synthetic data generation is increasingly important due to privacy concerns. While Autoencoder-based approaches have been widely used for this purpose, sampling from their latent s…
A Pseudo-labelling Auto-Encoder for unsupervised image classification
Aymene Mohammed Bouayed, Karim Atif, Rachid Deriche +1
In this paper, we introduce a unique variant of the denoising Auto-Encoder and combine it with the perceptual loss to classify images in an unsupervised manner. The proposed method…