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Found 2 papers, 1 papers with code
Accounting for the Sequential Nature of States to Learn Features for Reinforcement Learning
In this work, we investigate the properties of data that cause popular representation learning approaches to fail.
Overlooked Implications of the Reconstruction Loss for VAE Disentanglement
Our findings demonstrate the subjective nature of disentanglement and the importance of considering the interaction between the ground-truth factors, data and notably, the reconstruction loss, which is under-recognised in the literature.
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