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Learning deep autor...
Learning deep autoregressive models for hierarchical data
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- Andersson, Carl R. (author)
- Uppsala universitet,Avdelningen för systemteknik,Artificiell intelligens
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- Wahlström, Niklas, 1984- (author)
- Uppsala universitet,Avdelningen för systemteknik,Artificiell intelligens
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- Schön, Thomas B., Professor, 1977- (author)
- Uppsala universitet,Avdelningen för systemteknik,Artificiell intelligens
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(creator_code:org_t)
- Elsevier, 2021
- 2021
- English.
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In: IFAC PapersOnLine. - : Elsevier. - 2405-8963. ; , s. 529-534
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Abstract
Subject headings
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- We propose a model for hierarchical structured data as an extension to the stochastic temporal convolutional network. The proposed model combines an autoregressive model with a hierarchical variational autoencoder and downsampling to achieve superior computational complexity. We evaluate the proposed model on two different types of sequential data: speech and handwritten text. The results are promising with the proposed model achieving state-of-the-art performance.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
Keyword
- Deep learning
- variational autoencoders
- nonlinear systems
Publication and Content Type
- ref (subject category)
- kon (subject category)
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