624 citations · 1.4k across the 27 of their papers we have counts for
3 papers · 1 filter
Advancing Spatio-Temporal Processing in Spiking Neural Networks through Adaptation
Maximilian Baronig, Romain Ferrand, Silvester Sabathiel +1
Implementations of spiking neural networks on neuromorphic hardware promise orders of magnitude less power consumption than their non-spiking counterparts. The standard neuron mode…
Adaptive Robotic Arm Control with a Spiking Recurrent Neural Network on a Digital Accelerator
Alejandro Linares-Barranco, Luciano Prono, Robert Lengenstein +2
With the rise of artificial intelligence, neural network simulations of biological neuron models are being explored to reduce the footprint of learning and inference in resource-co…
Learning-to-learn enables rapid learning with phase-change memory-based in-memory computing
Thomas Ortner, Horst Petschenig, Athanasios Vasilopoulos +7
There is a growing demand for low-power, autonomously learning artificial intelligence (AI) systems that can be applied at the edge and rapidly adapt to the specific situation at d…