8 citations · 11 across the 3 of their papers we have counts for
3 papers · 1 filter
RAPNet: Accelerating Algebraic Multigrid with Learned Sparse Corrections
Yali Fink, Ido Ben-Yair, Lars Ruthotto +1
The scalable solution of large sparse linear systems is a bottleneck in scientific computing and graph analysis. While algebraic multigrid (AMG) offers optimal linear scaling, its…
Multigrid-Augmented Deep Learning Preconditioners for the Helmholtz Equation using Compact Implicit Layers
Bar Lerer, Ido Ben-Yair, Eran Treister
We present a deep learning-based iterative approach to solve the discrete heterogeneous Helmholtz equation for high wavenumbers. Combining classical iterative multigrid solvers and…
Quantized Convolutional Neural Networks Through the Lens of Partial Differential Equations
Ido Ben-Yair, Gil Ben Shalom, Moshe Eliasof +1
Quantization of Convolutional Neural Networks (CNNs) is a common approach to ease the computational burden involved in the deployment of CNNs, especially on low-resource edge devic…