all AI news
SMS: Spiking Marching Scheme for Efficient Long Time Integration of Differential Equations. (arXiv:2211.09928v1 [math.NA])
Nov. 21, 2022, 2:11 a.m. | Qian Zhang, Adar Kahana, George Em Karniadakis, Panos Stinis
cs.LG updates on arXiv.org arxiv.org
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 core element of the method is a SNN, trained to use
spike-encoded information about the solution at previous timesteps to predict
spike-encoded information at the next timestep. After the network has been
trained, it operates as an explicit numerical scheme that can be used to
compute the solution at future timesteps, given a spike-encoded initial
condition. …
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Data Engineer
@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania
Artificial Intelligence – Bioinformatic Expert
@ University of Texas Medical Branch | Galveston, TX
Lead Developer (AI)
@ Cere Network | San Francisco, US
Research Engineer
@ Allora Labs | Remote
Ecosystem Manager
@ Allora Labs | Remote
Founding AI Engineer, Agents
@ Occam AI | New York