Symbolic Disentangled Representations for Images
Alexandr Korchemnyi Aleksandr I. Panov Alexey K. Kovalev
作者信息
Abstract
The idea of disentangled representations is to reduce the data to a set of
generative factors that produce it. Typically, such representations are vectors
in latent space, where each coordinate corresponds to one of the generative
factors. The object can then be modified by changing the value of a particular
coordinate, but it is necessary to determine which coordinate corresponds to
the desired generative factor -- a difficult task if the vector representation
has a high dimension. In this article, we propose ArSyD (Architecture for
Symbolic Disentanglement), which represents each generative factor as a vector
of the same dimension as the resulting representation. In ArSyD, the object
representation is obtained as a superposition of the generative factor vector
representations. We call such a representation a \textit{symbolic disentangled
representation}. We use the principles of Hyperdimensional Computing (also
known as Vector Symbolic Architectures), where symbols are represented as
hypervectors, allowing vector operations on them. Disentanglement is achieved
by construction, no additional assumptions about the underlying distributions
are made during training, and the model is only trained to reconstruct images
in a weakly supervised manner. We study ArSyD on the dSprites and CLEVR
datasets and provide a comprehensive analysis of the learned symbolic
disentangled representations. We also propose new disentanglement metrics that
allow comparison of methods using latent representations of different
dimensions. ArSyD allows to edit the object properties in a controlled and
interpretable way, and the dimensionality of the object property representation
coincides with the dimensionality of the object representation itself.引用本文复制引用
Alexandr Korchemnyi,Aleksandr I. Panov,Alexey K. Kovalev.Symbolic Disentangled Representations for Images[EB/OL].(2024-12-25)[2026-04-03].https://arxiv.org/abs/2412.19847.学科分类
计算技术、计算机技术
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