1 citations · 1 across the 3 of their papers we have counts for
3 papers
math.NA2024
Attention-based hybrid solvers for linear equations that are geometry aware
Idan Versano, Eli Turkel
We present a novel architecture for learning geometry-aware preconditioners for linear partial differential equations (PDEs). We show that a deep operator network (Deeponet) can be…
cs.CV2023★ 1 cited
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…
cs.LG2022
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,…