124 citations · 657 across the 40 of their papers we have counts for
5 papers · 1 filter
Deep Knockoffs
Yaniv Romano, Matteo Sesia, Emmanuel J. Candès
This paper introduces a machine for sampling approximate model-X knockoffs for arbitrary and unspecified data distributions using deep generative models. The main idea is to iterat…
Unified Single-Image and Video Super-Resolution via Denoising Algorithms
Alon Brifman, Yaniv Romano, Michael Elad
Single Image Super-Resolution (SISR) aims to recover a high-resolution image from a given low-resolution version of it. Video Super Resolution (VSR) targets series of given images,…
MMSE Approximation For Sparse Coding Algorithms Using Stochastic Resonance
Dror Simon, Jeremias Sulam, Yaniv Romano +2
Sparse coding refers to the pursuit of the sparsest representation of a signal in a typically overcomplete dictionary. From a Bayesian perspective, sparse coding provides a Maximum…
Adversarial Noise Attacks of Deep Learning Architectures -- Stability Analysis via Sparse Modeled Signals
Yaniv Romano, Aviad Aberdam, Jeremias Sulam +1
Despite their impressive performance, deep convolutional neural networks (CNNs) have been shown to be sensitive to small adversarial perturbations. These nuisances, which one can b…
Acceleration of RED via Vector Extrapolation
Tao Hong, Yaniv Romano, Michael Elad
Models play an important role in inverse problems, serving as the prior for representing the original signal to be recovered. REgularization by Denoising (RED) is a recently introd…