YeonwooSung/GLOM
PyTorch implementation of GLOM
This is a PyTorch implementation of Geoffrey Hinton's GLOM architecture for neural networks, designed to process images. It takes raw image data and outputs hierarchical representations, allowing you to understand how different parts of an image relate to the whole. Machine learning researchers and practitioners working on advanced computer vision problems would use this to experiment with new image understanding paradigms.
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Use this if you are a machine learning researcher or developer experimenting with novel neural network architectures for image processing, particularly those interested in hierarchical part-whole relationships.
Not ideal if you need a plug-and-play solution for standard image classification or object detection, as this is a research implementation rather than a production-ready model.
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Language
Python
License
MIT
Category
Last pushed
Apr 01, 2022
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