dpernes/vae
Customisable Variational Autoencoder in PyTorch
This tool helps machine learning engineers and researchers explore and understand complex datasets by compressing data into a simpler, underlying representation and then reconstructing it. You input raw data, like images, and it outputs a compressed version as well as newly generated, similar data points. It's ideal for those working on data generation, anomaly detection, or dimensionality reduction tasks.
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Use this if you need a flexible way to customize and train a Variational Autoencoder model for tasks like generating new data samples or reducing the complexity of your datasets.
Not ideal if you require a different decoder architecture than the transposed version of your encoder, as this implementation imposes that constraint.
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Python
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Last pushed
Oct 31, 2018
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