Metadata-Version: 1.1
Name: GraphAttentionNetworks
Version: 0.1
Summary: A Graph Attention Framework for extracting Graph Attention embeddings and implementing Multihead Graph Attention Networks
Home-page: https://github.com/abhilash1910/GraphAttentionNetworks
Author: ABHILASH MAJUMDER
Author-email: debabhi1396@gmail.com
License: MIT
Download-URL: https://github.com/abhilash1910/GraphAttentionNetworks/archive/v_01.tar.gz
Description: This package is used for extracting Graph Attention Embeddings and provides a framework for a Tensorflow Graph Attention Layer which can be used for knowledge graph /node base semantic tasks. It determines the pair wise embedding matrix for a higher order node representation and concatenates them with an attention weight. It then passes it through a leakyrelu activation for importance sampling and damps out negative effect of a node.It then applies a softmax layer for normalization of the attention results and determines the final output scores.The GraphAttentionBase.py script implements a Tensorflow/Keras Layer for the GAT which can be used and the GraphMultiheadAttention.py is used to extract GAT embeddings.
Keywords: Anisotropic Embeddings,Graph Convolution Network,Graph Attention Network,Chebyshev networks,Higher order Graph embeddings,Multihead Graph Attention Framework,Tensorflow
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
