5 citations · 6 across the 5 of their papers we have counts for
5 papers
Blind Image Restoration via Fast Diffusion Inversion
Hamadi Chihaoui, Abdelhak Lemkhenter, Paolo Favaro
Image Restoration (IR) methods based on a pre-trained diffusion model have demonstrated state-of-the-art performance. However, they have two fundamental limitations: 1) they often…
SemiGPC: Distribution-Aware Label Refinement for Imbalanced Semi-Supervised Learning Using Gaussian Processes
Abdelhak Lemkhenter, Manchen Wang, Luca Zancato +3
In this paper we introduce SemiGPC, a distribution-aware label refinement strategy based on Gaussian Processes where the predictions of the model are derived from the labels poster…
Towards Sleep Scoring Generalization Through Self-Supervised Meta-Learning
Abdelhak Lemkhenter, Paolo Favaro
In this work we introduce a novel meta-learning method for sleep scoring based on self-supervised learning. Our approach aims at building models for sleep scoring that can generali…
Generative Adversarial Learning via Kernel Density Discrimination
Abdelhak Lemkhenter, Adam Bielski, Alp Eren Sari +1
We introduce Kernel Density Discrimination GAN (KDD GAN), a novel method for generative adversarial learning. KDD GAN formulates the training as a likelihood ratio optimization pro…
Boosting Generalization in Bio-Signal Classification by Learning the Phase-Amplitude Coupling
Abdelhak Lemkhenter, Paolo Favaro
Various hand-crafted features representations of bio-signals rely primarily on the amplitude or power of the signal in specific frequency bands. The phase component is often discar…