distance-encoding
GNN design framework
This repository provides an implementation of a novel framework for designing Graph Neural Networks (GNNs) with improved structural representation learning capabilities.
Distance Encoding for GNN Design
182 stars
8 watching
26 forks
Language: Jupyter Notebook
last commit: over 3 years ago Related projects:
Repository | Description | Stars |
---|---|---|
snap-stanford/graphgym | A platform for designing and evaluating Graph Neural Networks (GNN) models | 1,723 |
norse/norse | Deep learning framework for spiking neural networks | 673 |
chingyaoc/ggnn.pytorch | An implementation of a neural network architecture for processing graph-structured data and making predictions on nodes. | 465 |
mengcz13/kdd2021_cnfgnn | An implementation of a federated graph neural network for spatio-temporal modeling | 65 |
benedekrozemberczki/appnp | A PyTorch implementation of a graph neural network model that learns personalized node representations | 363 |
dawnranger/pytorch-agnn | An implementation of an attention-based graph neural network in PyTorch for semi-supervised learning | 145 |
tensorflow/gnn | Builds Graph Neural Networks on the TensorFlow platform using heterogeneous graphs and various machine learning techniques. | 1,369 |
benedekrozemberczki/sgcn | An implementation of a deep learning algorithm for graph data | 268 |
guillaume-chevalier/sgnn-self-governing-neural-networks-projection-layer | Reproduces a SGNN's word projections preprocessing pipeline using word n-grams instead of skip-grams | 23 |
benedekrozemberczki/pytorch_geometric_temporal | A PyTorch extension for building temporal graph neural networks with support for recurrent and attention-based models | 2,677 |
benedekrozemberczki/simgnn | An implementation of SimGNN, a neural network approach to computing graph similarity | 759 |
benedekrozemberczki/capsgnn | A PyTorch implementation of a graph neural network architecture | 1,246 |
deepgraphlearning/gmnn | A software framework that integrates statistical relational learning and graph neural networks for semi-supervised object classification and unsupervised node representation learning. | 401 |
fedml-ai/spreadgnn | A framework for decentralized multi-task learning of graph neural networks on molecular data with guaranteed convergence | 44 |
carpedm20/discogan-pytorch | A PyTorch implementation of a Generative Adversarial Network (GAN) for discovering cross-domain relations. | 1,084 |