3 papers
cs.LG2026
Fully Trainable Deep Differentiable Logic Gate Networks and Lookup Table Networks
Wout Mommen, Lars Keuninckx, Matthias Hartmann +2
We introduce a novel method for both partial and full optimization of the connections in deep differentiable logic gate networks (LGNs) and lookup table networks (LUTNs). Our train…
cs.CV2023
An Encoding Framework for Binarized Images using HyperDimensional Computing
Laura Smets, Werner Van Leekwijck, Ing Jyh Tsang +1
Hyperdimensional Computing (HDC) is a brain-inspired and light-weight machine learning method. It has received significant attention in the literature as a candidate to be applied…
cs.NE2023
Co-learning synaptic delays, weights and adaptation in spiking neural networks
Lucas Deckers, Laurens Van Damme, Ing Jyh Tsang +2
Spiking neural networks (SNN) distinguish themselves from artificial neural networks (ANN) because of their inherent temporal processing and spike-based computations, enabling a po…