898 citations · 965 across the 11 of their papers we have counts for
7 papers · 1 filter
Single Neuromorphic Memristor closely Emulates Multiple Synaptic Mechanisms for Energy Efficient Neural Networks
Christoph Weilenmann, Alexandros Ziogas, Till Zellweger +6
Biological neural networks do not only include long-term memory and weight multiplication capabilities, as commonly assumed in artificial neural networks, but also more complex fun…
Hebbian Deep Learning Without Feedback
Adrien Journé, Hector Garcia Rodriguez, Qinghai Guo +1
Recent approximations to backpropagation (BP) have mitigated many of BP's computational inefficiencies and incompatibilities with biology, but important limitations still remain. M…
Short-Term Plasticity Neurons Learning to Learn and Forget
Hector Garcia Rodriguez, Qinghai Guo, Timoleon Moraitis
Short-term plasticity (STP) is a mechanism that stores decaying memories in synapses of the cerebral cortex. In computing practice, STP has been used, but mostly in the niche of sp…
Spike-inspired Rank Coding for Fast and Accurate Recurrent Neural Networks
Alan Jeffares, Qinghai Guo, Pontus Stenetorp +1
Biological spiking neural networks (SNNs) can temporally encode information in their outputs, e.g. in the rank order in which neurons fire, whereas artificial neural networks (ANNs…
Optimality of short-term synaptic plasticity in modelling certain dynamic environments
Timoleon Moraitis, Abu Sebastian, Evangelos Eleftheriou
Biological neurons and their in-silico emulations for neuromorphic artificial intelligence (AI) use extraordinarily energy-efficient mechanisms, such as spike-based communication a…
File Classification Based on Spiking Neural Networks
Ana Stanojevic, Giovanni Cherubini, Timoleon Moraitis +1
In this paper, we propose a system for file classification in large data sets based on spiking neural networks (SNNs). File information contained in key-value metadata pairs is map…
Fatiguing STDP: Learning from Spike-Timing Codes in the Presence of Rate Codes
Timoleon Moraitis, Abu Sebastian, Irem Boybat +3
Spiking neural networks (SNNs) could play a key role in unsupervised machine learning applications, by virtue of strengths related to learning from the fine temporal structure of e…