9 citations · 11 across the 3 of their papers we have counts for
4 papers
Online Continual Learning on Intel Loihi 2 via a Co-designed Spiking Neural Network
Elvin Hajizada, Danielle Rager, Timothy Shea +5
Edge AI must adapt to new classes and shifting data within a tight power budget, but online continual learning (learning from each sample before the next arrives) is where conventi…
A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware
Philipp Plank, Arjun Rao, Andreas Wild +1
Spike-based neuromorphic hardware holds the promise to provide more energy efficient implementations of Deep Neural Networks (DNNs) than standard hardware such as GPUs. But this re…
NxTF: An API and Compiler for Deep Spiking Neural Networks on Intel Loihi
Bodo Rueckauer, Connor Bybee, Ralf Goettsche +3
Spiking Neural Networks (SNNs) are a promising paradigm for efficient event-driven processing of spatio-temporally sparse data streams. SNNs have inspired the design and can take a…
Neuromorphic Nearest-Neighbor Search Using Intel's Pohoiki Springs
E. Paxon Frady, Garrick Orchard, David Florey +7
Neuromorphic computing applies insights from neuroscience to uncover innovations in computing technology. In the brain, billions of interconnected neurons perform rapid computation…