CapsNet and CapsGNN
About CapsNet
loretoparisi/CapsNet
CapsNet (Capsules Net) in Geoffrey E Hinton paper "Dynamic Routing Between Capsules" - State Of the Art
This project offers a collection of implementations and resources for Capsule Networks (CapsNets), a type of neural network capable of recognizing objects more effectively than traditional Convolutional Neural Networks, especially in complex scenarios. It takes image data as input and outputs highly accurate object classifications, even when objects overlap. Data scientists and machine learning researchers exploring advanced computer vision techniques would use this project.
About CapsGNN
benedekrozemberczki/CapsGNN
A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).
This tool helps machine learning researchers categorize complex structures by analyzing their connections and properties. It takes descriptions of graphs (like social networks or molecular structures) with their nodes, connections, and labels as input. The output is a classification that tells you what type of graph it is. Researchers working on graph classification problems, particularly those interested in advanced neural network architectures, would use this.
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