Kaixhin/Autoencoders
Torch implementations of various types of autoencoders
This repository provides working code examples for various autoencoder models, which are neural networks used for unsupervised learning of efficient data codings. You input raw data like images or text sequences, and the autoencoder learns to compress it into a smaller representation and then reconstruct it, effectively performing feature extraction and denoising. Data scientists, machine learning engineers, and researchers would use this to understand and implement different autoencoder architectures.
476 stars. No commits in the last 6 months.
Use this if you are a machine learning practitioner looking for a reference implementation of a specific autoencoder architecture for tasks like data compression, dimensionality reduction, or anomaly detection.
Not ideal if you need a high-level library that abstracts away the implementation details, or if you require extensive documentation and tutorials on the underlying theory.
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476
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Language
Lua
License
MIT
Last pushed
Aug 28, 2017
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