9 citations · 19 across the 7 of their papers we have counts for
7 papers
The Singularity Space: A Generative Diffusion Framework for Signal Representation
Eli Bar-Yosef, Amir Averbuch, Eli Turkel
Generative models often represent signals as dense grids of amplitudes, blurring sharp transients that are crucial for the correctness of physical signals. We introduce Singularity…
Real-time Inference and Extrapolation via a Diffusion-inspired Temporal Transformer Operator (DiTTO)
Oded Ovadia, Vivek Oommen, Adar Kahana +3
Extrapolation remains a grand challenge in deep neural networks across all application domains. We propose an operator learning method to solve time-dependent partial differential…
ViTO: Vision Transformer-Operator
Oded Ovadia, Adar Kahana, Panos Stinis +2
We combine vision transformers with operator learning to solve diverse inverse problems described by partial differential equations (PDEs). Our approach, named ViTO, combines a U-N…
A physically-informed Deep-Learning approach for locating sources in a waveguide
Adar Kahana, Symeon Papadimitropoulos, Eli Turkel +1
Inverse source problems are central to many applications in acoustics, geophysics, non-destructive testing, and more. Traditional imaging methods suffer from the resolution limit,…
Blending Neural Operators and Relaxation Methods in PDE Numerical Solvers
Enrui Zhang, Adar Kahana, Alena Kopaničáková +4
Neural networks suffer from spectral bias having difficulty in representing the high frequency components of a function while relaxation methods can resolve high frequencies effici…
A Convolutional Dispersion Relation Preserving Scheme for the Acoustic Wave Equation
Oded Ovadia, Adar Kahana, Eli Turkel
We propose an accurate numerical scheme for approximating the solution of the two dimensional acoustic wave problem. We use machine learning to find a stencil suitable even in the…
Non-iterative domain decomposition for the Helmholtz equation using the method of difference potentials
Evan North, Semyon Tsynkov, Eli Turkel
We use the Method of Difference Potentials (MDP) to solve a non-overlapping domain decomposition formulation of the Helmholtz equation. The MDP reduces the Helmholtz equation on ea…