Adaptive Optical Dendrites

Resultado final

Update data management plan
Report on dendritic functionalities allowing adaptive dendritic computation using multi-branched dendrites

This deliverable will report on how to include adaptation (synaptic plasticity) into the multiple branched dendritic models for use on optic fibers.

Report on principles of context-dependent computations with networks of dendritic units

"This deliverable will report on how to include ""context"" into the computations that can be performed with networks of dendritic units. Context can render an important piece of information for solving complex spatio-temporal problems and larger networks of ODUs should be able to handle this, too."

Report on the definition of KPIs

This deliverable deals with the definition and description of possible Key Performance Indices KPIs for ADOPD It it foreseen to critically rereview the usefulness of the heredefined KPIs at month 18 in the Periodic Report and possibly amend them following the needs of the project

Update Dissemination and Expoitation Plan

Update of Dissemination and Explotation Plan

Report on gradient-based optimization techniques for networks of dendritic units

This is the first report where we will address larger networks of dendritic units Here we will address the question how to use different optimization methods gradientbased for achieving convergence when faced with different tasks

Report on dendritic functionalities allowing adaptive dendritic computation using single-branched dendrites

This deliverable will report on how to include adaptation synaptic plasticity into the single branch dendritic models for use on optic fibers

Benchmarking Report

This is the report on system performance in view of the KPIs defined in deliverable D5.3 (and potentially revised in the periodic report at month 18).

Report on first non-linear model of transfer to optical systems

This deliverable will report on how to transfer a nonlinear synapticdendritic model to the optical fiber systems single mode fibers

Dissemination and Explotation plan

Dissemination and Exploitation Plan

Project Flyer

This deliverable will be a flyer for dissemination to potentially interested parties in science and industry

Internal Workshop

Towards the end of the project we will organize a targeted workshop with a selected group of external participants. We plant to use a small part of the budget from every partner to cover the costs for this WS.

Project Web site

Project Web site with Logo up and running Contains public and private area

Report on data management plan

This deliverable will report on the data management plan of ADOPD according the OpenResearch Data Pilot

Publicaciones

Combining optimal path search with task-dependent learning in a neural network

Autores: Tomas Kulvicius, Minija Tamosiunaite, Florentin Wörgötter
Publicado en: arxiv, 2022
Editor: arxiv
DOI: 10.48550/arxiv.2201.11104

A normative framework for learning top-down predictions through synaptic plasticity in apical dendrites

Autores: Rao, A., Legenstein, R., Subramoney, A. and Maass, W.
Publicado en: 2021
Editor: biorxiv
DOI: 10.1101/2021.03.04.433822

Synapses learn to utilize pre-synaptic noise for the prediction of postsynaptic dynamics

Autores: David Kappel; Christian Tetzlaff
Publicado en: biorxiv, Edición 15, 2022
Editor: biorxiv
DOI: 10.1101/2022.04.22.489175

Experimental multi-bit header classification at 28.5 Gb/s with step-index few-mode fibers

Autores: Pflüger, M., Ortín, S., Leininger, L., Mirasso, C.R., Argyris, A.
Publicado en: techrxiv, 2024
Editor: techrxiv
DOI: 10.36227/techrxiv.170974154.49785806/v2

Microring resonators with external optical feedback for time delay reservoir computing

Autores: Giovanni Donati; Claudio R. Mirasso; Mattia Mancinelli; Lorenzo Pavesi; Apostolos Argyris
Publicado en: Optics Express, Edición 30, 2022, Página(s) 522-537, ISSN 1094-4087
Editor: Optical Society of America
DOI: 10.1364/oe.444063

Differential Hebbian learning with time-continuous signals for active noise reduction

Autores: Konstantin Möller; David Kappel; Minija Tamosiunaite; Christian Tetzlaff; Bernd Porr; Florentin Wörgötter
Publicado en: PLoS One, Edición 1, 2022, ISSN 1932-6203
Editor: Public Library of Science
DOI: 10.1371/journal.pone.0266679

Dendritic Computing: Branching Deeper into Machine Learning

Autores: Acharya, J., Basu, A., Legenstein, R., Limbacher, T., Poirazi, P., and Wu, X.
Publicado en: Neuroscience, 2021, ISSN 0306-4522
Editor: Elsevier BV
DOI: 10.1016/j.neuroscience.2021.10.001

Optical dendrites for spatio-temporal computing with few-mode fibers

Autores: Ortín González, Silvia; Soriano, Miguel C.; Fischer, Ingo; Mirasso, Claudio R.; Argyris, Apostolos
Publicado en: Optical Materials Express, Edición 12, 2022, Página(s) 1907-1919, ISSN 2159-3930
Editor: Optical Society of America
DOI: 10.1364/ome.453506

Bootstrapping Concept Formation in Small Neural Networks

Autores: Tamosiunaite, M., Kulvicius, T., Wörgötter, F.
Publicado en: IEEE Transactions on Cognitive and Developmental Systems, 2021, ISSN 2379-8920
Editor: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/tcds.2022.3163022

Unsupervised learning of perceptual feature combinations

Autores: Tamosiunaite, Minija; Tetzlaff, Christian; Wörgötter, Florentin; Bush, Daniel
Publicado en: PLoS Computational Biology, Edición 20(3), 2024, ISSN 1553-734X
Editor: Public Library of Science
DOI: 10.1371/journal.pcbi.1011926

Context association in pyramidal neurons through local synaptic plasticity in apical dendrites

Autores: Maximilian Baronig; Robert Legenstein
Publicado en: Frontiers in Neuroscience, Vol 17 (2024), Edición 9, 2024, ISSN 1662-453X
Editor: Frontiers
DOI: 10.3389/fnins.2023.1276706

Implementation of input correlation learning with an optoelectronic dendritic unit

Autores: Silvia Ortín; Miguel C. Soriano; Christian Tetzlaff; Florentin Wörgötter; Ingo Fischer; Claudio R. Mirasso; Apostolos Argyris
Publicado en: Frontiers in Physics, Edición 11, 2023, Página(s) 1112295, ISSN 2296-424X
Editor: Frontiers Media
DOI: 10.3389/fphy.2023.1112295

nMNSD—A Spiking Neuron-Based Classifier That Combines Weight-Adjustment and Delay-Shift

Autores: Susi, G., Antón-Toro, L.F., Maestú, F., Pereda, E. and Mirasso, C.
Publicado en: Frontiers in Neuroscience, 2021, ISSN 1662-4548
Editor: Frontiers Research Foundation
DOI: 10.3389/fnins.2021.582608

Learn one size to infer all: Exploiting translational symmetries in delay-dynamical and spatiotemporal systems using scalable neural networks

Autores: Mirko Goldmann, Claudio R. Mirasso, Ingo Fischer, and Miguel C. Soriano
Publicado en: Physical Review E, Edición 106, 2022, Página(s) 044211, ISSN 1539-3755
Editor: American Physical Society
DOI: 10.1103/physreve.106.044211

Unveiling the role of plasticity rules in reservoir computing

Autores: Morales, G.B., Mirasso, C.R. and Soriano, M.C.
Publicado en: Neurocomputing, Edición 461, 2021, Página(s) 705-715, ISSN 0925-2312
Editor: Elsevier BV
DOI: 10.1016/j.neucom.2020.05.127

Photonic neuromorphic technologies in optical communications

Autores: Argyris, Apostolos
Publicado en: Nanophotonics, Edición 11, 2022, ISSN 2192-8614
Editor: Walter de Gruyter
DOI: 10.1515/nanoph-2021-0578

Resultado final

Publicaciones

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