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INFORMATION THEORY GUIDED SEQUENTIAL REPRESENTATION DISENTANGLEMENT AND DATA GENERATION
INFORMATION THEORY GUIDED SEQUENTIAL REPRESENTATION DISENTANGLEMENT AND DATA GENERATION
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机译:信息论指导的序列表示解纠缠和数据生成
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摘要
A computer-implemented method for representation disentanglement is provided. The method includes encoding an input vector into an embedding. The method further includes learning, by a hardware processor, disentangled representations of the input vector including a style embedding and a content embedding by performing sample-based mutual information minimization on the embedding under a Wasserstein distance regularization and a Kullback-Leibler (KL) divergence. The method also includes decoding the style and content embeddings to obtain a reconstructed vector.
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