latest | popular

Filter by
Deep Learning With Graph-Structured Representations
Novel approaches based on the theme of structuring the representations and computations of neural network-based models in the form of a graph.
graph-neural-networks graph-convolutional-networks graph-auto-encoders relational-graph-convolutional-networks
TF Geometric
Efficient and Friendly Graph Neural Network Library for TensorFlow 1.x and 2.x.
graph-neural-networks graph-convolutional-networks tensorflow code
ProteinGCN: Protein model quality assessment using GCNs
Source code for the paper: ProteinGCN: Protein model quality assessment using Graph Convolutional Networks.
protein-model-quality-estimation graph-convolutional-networks graph-neural-networks pytorch
Message Passing Query Embedding
MPQE is a model for answering complex queries over knowledge graphs, that learns embeddings of entities in the knowledge graph, & embeddings for variable ...
graph-neural-networks graph-convolutional-networks knowledge-graphs mpqe
ASAP: Pooling for Graph Neural Network (AAAI 2020)
ASAP is a sparse and differentiable pooling method that addresses the limitations of previous graph pooling layers.
graph-neural-networks graph-classification pool self-attention
Machine Learning on Graphs: A Model and Comprehensive Taxonomy
We propose a simple framework (GraphEDM) and a comprehensive Taxonomy to review and unify several graph representation learning methods.
graph-neural-networks graph-convolutional-networks autoencoders graph-regularization
projects 1 - 10 of 23
Topic experts
Share a project
Share something you or the community has made with ML.