pytorch_geometric_signed_directed
Graph neural network library
A PyTorch Geometric extension library for working with signed and directed graphs
PyTorch Geometric Signed Directed is a signed/directed graph neural network extension library for PyTorch Geometric. The paper is accepted by LoG 2023.
131 stars
7 watching
17 forks
Language: Python
last commit: about 2 years agoLinked from 2 awesome lists
deep-learningdirected-networksgnngraph-neural-netowrksmachine-learningnetworkspythonpytorchpytorch-geometricsigned-networks
bharathgs/awesome-pytorch-list
krzjoa/awesome-python-data-scienceRelated projects:
| Repository | Description | Stars |
|---|---|---|
 chingyaoc/ggnn.pytorch | An implementation of a neural network architecture for processing graph-structured data and making predictions on nodes. | 466 |
 benedekrozemberczki/pytorch_geometric_temporal | A PyTorch extension for building temporal graph neural networks with support for recurrent and attention-based models | 2,694 |
| sherylhyx/sssnet_signed_clustering | Semi-supervised signed network clustering algorithm | 24 |
| benedekrozemberczki/sgcn | An implementation of a deep learning algorithm for graph data | 270 |
| benedekrozemberczki/capsgnn | A PyTorch implementation of a graph neural network architecture | 1,246 |
 kimhc6028/relational-networks | A PyTorch implementation of a neural network module for relational reasoning in computer vision tasks | 809 |
 dyhan0920/pyramidnet-pytorch | An implementation of a deep neural network architecture for image classification tasks | 273 |
 bupt-gamma/openhgnn | An open-source toolkit for training and applying heterogeneous graph neural networks using PyTorch and the Deep Graph Library. | 879 |
 dawnranger/pytorch-agnn | An implementation of an attention-based graph neural network in PyTorch for semi-supervised learning | 146 |
| benedekrozemberczki/clustergcn | A PyTorch implementation of a clustering algorithm for graph neural networks | 788 |
| benedekrozemberczki/appnp | A PyTorch implementation of a graph neural network model that learns personalized node representations | 367 |
 norse/norse | Deep learning framework for spiking neural networks | 685 |
| benedekrozemberczki/seal-ci | A PyTorch implementation of a semi-supervised graph classification model that learns hierarchical representations from labeled and unlabeled graph data. | 209 |
 xternalz/wideresnet-pytorch | An implementation of Wide Residual Networks in PyTorch for efficient deep learning on CIFAR10/100 datasets. | 334 |
 4uiiurz1/pytorch-res2net | Implementations of deep learning architectures using PyTorch for image classification tasks on various datasets. | 112 |