id:"swepub:oai:DiVA.org:kth-292966"
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- Ravichandran, Naresh BalajiKTH,Beräkningsvetenskap och beräkningsteknik (CST),Computat Brain Sci Lab (author)
Learning representations in Bayesian Confidence Propagation neural networks
- Article/chapterEnglish2020
Publisher, publication year, extent ...
- IEEE,2020
- printrdacarrier
Numbers
- LIBRIS-ID:oai:DiVA.org:kth-292966
- https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-292966URI
- https://doi.org/10.1109/IJCNN48605.2020.9207061DOI
Supplementary language notes
- Language:English
- Summary in:English
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Notes
- QC 20210419
- Unsupervised learning of hierarchical representations has been one of the most vibrant research directions in deep learning during recent years. In this work we study biologically inspired unsupervised strategies in neural networks based on local Hebbian learning. We propose new mechanisms to extend the Bayesian Confidence Propagating Neural Network (BCPNN) architecture, and demonstrate their capability for unsupervised learning of salient hidden representations when tested on the MNIST dataset.
Subject headings and genre
- NATURVETENSKAP Data- och informationsvetenskap hsv//swe
- NATURAL SCIENCES Computer and Information Sciences hsv//eng
- neural networks
- brain-like computing
- bio-inspired
- unsupervised learning
- structural plasticity
Added entries (persons, corporate bodies, meetings, titles ...)
- Lansner, Anders,ProfessorKTH,Beräkningsvetenskap och beräkningsteknik (CST),Computat Brain Sci Lab(Swepub:kth)u12s8cr8 (author)
- Herman, Pawel,1979-KTH,Beräkningsvetenskap och beräkningsteknik (CST),Computat Brain Sci Lab(Swepub:kth)u19pqm1e (author)
- KTHBeräkningsvetenskap och beräkningsteknik (CST) (creator_code:org_t)
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- In:2020 International joint conference on neural networks (IJCNN): IEEE
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