License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.08041.1
URN: urn:nbn:de:0030-drops-14250
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2008/1425/
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De Raedt, Luc ; Hammer, Barbara ; Hitzler, Pascal ; Maass, Wolfgang

08041 Abstracts Collection -- Recurrent Neural Networks - Models, Capacities, and Applications

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08041_abstracts_collection.1425.pdf (0.2 MB)

Abstract

From January 20 to 25 2008, the Dagstuhl Seminar 08041 ``Recurrent Neural Networks- Models, Capacities, and Applications'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl.
During the seminar, several participants presented their current
research, and ongoing work and open problems were discussed. Abstracts of
the presentations given during the seminar as well as abstracts of
seminar results and ideas are put together in this paper. The first section
describes the seminar topics and goals in general.
Links to extended abstracts or full papers are provided, if available.

BibTeX - Entry

@InProceedings{deraedt_et_al:DagSemProc.08041.1,
  author =	{De Raedt, Luc and Hammer, Barbara and Hitzler, Pascal and Maass, Wolfgang},
  title =	{{08041 Abstracts Collection – Recurrent Neural Networks - Models, Capacities, and Applications}},
  booktitle =	{Recurrent Neural Networks- Models, Capacities, and Applications},
  pages =	{1--16},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8041},
  editor =	{Luc De Raedt and Barbara Hammer and Pascal Hitzler and Wolfgang Maass},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2008/1425},
  URN =		{urn:nbn:de:0030-drops-14250},
  doi =		{10.4230/DagSemProc.08041.1},
  annote =	{Keywords: Recurrent Neural Networks, Neural-Symbolic Integration, Biological Models, Hybrid Models, Relational Learning Echo State Networks, Spike Prediction, Unsupervised Recurrent Networks}
}

Keywords: Recurrent Neural Networks, Neural-Symbolic Integration, Biological Models, Hybrid Models, Relational Learning Echo State Networks, Spike Prediction,
Freie Schlagwörter (deutsch): Unsupervised Recurrent Networks
Collection: 08041 - Recurrent Neural Networks- Models, Capacities, and Applications
Issue Date: 2008
Date of publication: 15.04.2008

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