4 citations · 9 across the 6 of their papers we have counts for
7 papers
On the Relation Between Linear Diffusion and Power Iteration
Dana Weitzner, Mauricio Delbracio, Peyman Milanfar +1
Recently, diffusion models have gained popularity due to their impressive generative abilities. These models learn the implicit distribution given by the training dataset, and samp…
On The Relationship Between Universal Adversarial Attacks And Sparse Representations
Dana Weitzner, Raja Giryes
The prominent success of neural networks, mainly in computer vision tasks, is increasingly shadowed by their sensitivity to small, barely perceivable adversarial perturbations in i…
AI Increases Global Access to Reliable Flood Forecasts
Grey Nearing, Deborah Cohen, Vusumuzi Dube +15
Floods are one of the most common natural disasters, with a disproportionate impact in developing countries that often lack dense streamflow gauge networks. Accurate and timely war…
Neural (Tangent Kernel) Collapse
Mariia Seleznova, Dana Weitzner, Raja Giryes +2
This work bridges two important concepts: the Neural Tangent Kernel (NTK), which captures the evolution of deep neural networks (DNNs) during training, and the Neural Collapse (NC)…
Flood forecasting with machine learning models in an operational framework
Sella Nevo, Efrat Morin, Adi Gerzi Rosenthal +28
The operational flood forecasting system by Google was developed to provide accurate real-time flood warnings to agencies and the public, with a focus on riverine floods in large,…
Separable Joint Blind Deconvolution and Demixing
Dana Weitzner, Raja Giryes
Blind deconvolution and demixing is the problem of reconstructing convolved signals and kernels from the sum of their convolutions. This problem arises in many applications, such a…
Face Authentication from Grayscale Coded Light Field
Dana Weitzner, David Mendlovic, Raja Giryes
Face verification is a fast-growing authentication tool for everyday systems, such as smartphones. While current 2D face recognition methods are very accurate, it has been suggeste…