LGFeb 26, 2023
Autoencoders as Pattern Filters
arXiv:2302.13393v1h-index: 16
Originality Synthesis-oriented
AI Analysis
This work addresses pattern filtering and classification in machine learning, but appears incremental as it builds on existing autoencoder methods.
The authors tackled the problem of transforming autoencoders into pattern filters, and demonstrated that this approach can also be used to build robust classifiers by learning to filter patterns of specific classes.
We discuss a simple approach to transform autoencoders into "pattern filters". Besides filtering, we show how this simple approach can be used also to build robust classifiers, by learning to filter only patterns of a given class.