9 citations · 34 across the 15 of their papers we have counts for
5 papers · 1 filter
Analysis of biologically plausible neuron models for regression with spiking neural networks
Mario De Florio, Adar Kahana, George Em Karniadakis
This paper explores the impact of biologically plausible neuron models on the performance of Spiking Neural Networks (SNNs) for regression tasks. While SNNs are widely recognized f…
SMS: Spiking Marching Scheme for Efficient Long Time Integration of Differential Equations
Qian Zhang, Adar Kahana, George Em Karniadakis +1
We propose a Spiking Neural Network (SNN)-based explicit numerical scheme for long time integration of time-dependent Ordinary and Partial Differential Equations (ODEs, PDEs). The…
On the Geometry Transferability of the Hybrid Iterative Numerical Solver for Differential Equations
Adar Kahana, Enrui Zhang, Somdatta Goswami +3
The discovery of fast numerical solvers prompted a clear and rapid shift towards iterative techniques in many applications, especially in computational mechanics, due to the increa…
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…