Denoising without access to clean data using a partitioned autoencoder

Training a denoising autoencoder neural network requires access to truly clean data, a requirement which is often impractical. To remedy this, we introduce a method to train an autoencoder using only noisy data, having examples with and without the signal class of interest.

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Dan Stowell, Richard E. Turner (2024). Dataset: Denoising without access to clean data using a partitioned autoencoder. https://doi.org/10.57702/4942gjnp

DOI retrieved: December 16, 2024

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Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.1509.05982
Author Dan Stowell
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Richard E. Turner
Homepage https://arxiv.org/abs/1509.07055