Eleni Vasilaki

According to our database1, Eleni Vasilaki authored at least 48 papers between 2003 and 2024.

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In proceedings 
PhD thesis 


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On csauthors.net:


Optimising network interactions through device agnostic models.
CoRR, 2024

Editorial: Focus issue on energy-efficient neuromorphic devices, systems and algorithms.
Neuromorph. Comput. Eng., December, 2023

Machine learning using magnetic stochastic synapses.
Neuromorph. Comput. Eng., June, 2023

SpaRCe: Improved Learning of Reservoir Computing Systems Through Sparse Representations.
IEEE Trans. Neural Networks Learn. Syst., February, 2023

Modelling novelty detection in the thalamocortical loop.
PLoS Comput. Biol., 2023

EchoVPR: Echo State Networks for Visual Place Recognition.
IEEE Robotics Autom. Lett., 2022

Signal neutrality, scalar property, and collapsing boundaries as consequences of a learned multi-timescale strategy.
PLoS Comput. Biol., 2022

A perspective on physical reservoir computing with nanomagnetic devices.
CoRR, 2022

A semi-supervised sparse K-Means algorithm.
Pattern Recognit. Lett., 2021

An empirical comparison between stochastic and deterministic centroid initialisation for K-means variations.
Mach. Learn., 2021

Quantifying the Computational Capability of a Nanomagnetic Reservoir Computing Platform with Emergent Magnetization Dynamics.
CoRR, 2021

EchoVPR: Echo State Networks for Visual Place Recognition.
CoRR, 2021

A Robotic Model of Hippocampal Reverse Replay for Reinforcement Learning.
CoRR, 2021

An alternative to backpropagation through time.
Nat. Mach. Intell., 2020

Exploiting Multiple Timescales in Hierarchical Echo State Networks.
Frontiers Appl. Math. Stat., 2020

Memristors - from In-memory computing, Deep Learning Acceleration, Spiking Neural Networks, to the Future of Neuromorphic and Bio-inspired Computing.
CoRR, 2020

Memristors - From In-Memory Computing, Deep Learning Acceleration, and Spiking Neural Networks to the Future of Neuromorphic and Bio-Inspired Computing.
Adv. Intell. Syst., 2020

Fast Reverse Replays of Recent Spatiotemporal Trajectories in a Robotic Hippocampal Model.
Proceedings of the Biomimetic and Biohybrid Systems - 9th International Conference, 2020

SpaRCe: Sparse reservoir computing.
CoRR, 2019

Learning sparsity in reservoir computing through a novel bio-inspired algorithm.
CoRR, 2019

Robots that Imagine - Can Hippocampal Replay Be Utilized for Robotic Mnemonics?
Proceedings of the Biomimetic and Biohybrid Systems - 8th International Conference, 2019

Abstract concept learning in a simple neural network inspired by the insect brain.
PLoS Comput. Biol., 2018

A generalised framework for detailed classification of swimming paths inside the Morris Water Maze.
CoRR, 2017

Is Epicurus the father of Reinforcement Learning?
CoRR, 2017

An inexpensive flying robot design for embodied robotics research.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

A Model for an Angular Velocity-Tuned Motion Detector Accounting for Deviations in the Corridor-Centering Response of the Bee.
PLoS Comput. Biol., 2016

Modelling Stock-market Investors as Reinforcement Learning Agents [Correction].
CoRR, 2016

Emulating long-term synaptic dynamics with memristive devices.
CoRR, 2015

Detection of multiple and overlapping bidirectional communities within large, directed and weighted networks of neurons.
CoRR, 2015

Emulating short-term synaptic dynamics with memristive devices.
CoRR, 2015

Highly scalable parallel processing of extracellular recordings of Multielectrode Arrays.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

Modelling stock-market investors as Reinforcement Learning agents.
Proceedings of the 2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems, 2015

QSpike tools: a generic framework for parallel batch preprocessing of extracellular neuronal signals recorded by substrate microelectrode arrays.
Frontiers Neuroinformatics, 2014

Adaptation of short-term plasticity parameters via error-driven learning may explain the correlation between activity-dependent synaptic properties, connectivity motifs and target specificity.
Frontiers Comput. Neurosci., 2014

Memristors as synapse emulators in the context of event-based computation.
Proceedings of the IEEE International Symposium on Circuits and Systemss, 2014

Transient and steady-state selection in the striatal microcircuit.
Frontiers Comput. Neurosci., 2013

The Green Brain Project - Developing a Neuromimetic Robotic Honeybee.
Proceedings of the Biomimetic and Biohybrid Systems, 2013

Temporal processing with volatile memristors.
Proceedings of the 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), 2013

Emergence of Connectivity Patterns from Long-Term and Short-Term Plasticities.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

How Degrading Networks Can Increase Cognitive Functions.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail.
PLoS Comput. Biol., 2009

Adaptive Gain Modulation in V1 Explains Contextual Modifications during Bisection Learning.
PLoS Comput. Biol., 2009

Stimulus sampling as an exploration mechanism for fast reinforcement learning.
Biol. Cybern., 2009

Learning flexible sensori-motor mappings in a complex network.
Biol. Cybern., 2009

Tag-Trigger-Consolidation: A Model of Early and Late Long-Term-Potentiation and Depression.
PLoS Comput. Biol., 2008

Perceptual Learning via Modification of Cortical Top-Down Signals.
PLoS Comput. Biol., 2007

A biologically inspired dynamic model for vision.
PhD thesis, 2003

Temporal album.
IEEE Trans. Neural Networks, 2003