🚀 The feature, motivation and pitch I am working with heterogeneous knowledge graphs and am trying to do link prediction on them. The specific issue I am facing is that I cannot find any working implementation that would allow me to do l...
Name Last commit message Last commit date Latest commit lijunliang update Aug 30, 2023 6d4848d·Aug 30, 2023 History 3 Commits .idea data heterogeneous homogeneous models README.md models.py pytorchtools.py util.py README GNNs-for-Link-Prediction ...
Stanford University and many great external contributors. With this, we are releasingPyG 2.0, a new major release that brings sophisticatedheterogeneous graph support,GraphGym integrationandmany other exciting features
: Heterogeneous Graph Transformer (https://github.com/pyg-team/pytorch_geometric/blob/master/examples/hetero/hgt_dblp.pyxamples/hetero/hgt_dblp.py)] HEATConv from Mo et al.: Heterogeneous Edge-Enhanced Graph Attention Network For Multi-Agent Trajectory Prediction (CoRR 2021) SSGConv from Zhu et...
We focus on the need of GNN applications in challenging real-world scenarios, and support learning on diverse types of graphs, including but not limited to: scalable GNNs for graphs with millions of nodes; dynamic GNNs for node predictions over time; heterogeneous GNNs with multiple node types ...
Heterogeneous GraphSAGE for movie recommendations pytorch recsys pyg graphsage gnn Updated Jun 11, 2024 Jupyter Notebook AlbertoFormaggio1 / fine_tuning_classification_prediction_GNN Star 0 Code Issues Pull requests Empirical Research over the possible advantages of pretraining a Graph Neural Net...
HEATConvfrom Moet al.:Heterogeneous Edge-Enhanced Graph Attention Network For Multi-Agent Trajectory Prediction(CoRR 2021) SSGConvfrom Zhuet al.:Simple Spectral Graph Convolution(ICLR 2021) FusedGATConvfrom Zhanget al.:Understanding GNN Computational Graph: A Coordinated Computation, IO, and Memory Pe...
Edge-level temporal sampling on a heterogeneous graph with distributed training (examples/distributed/pyg/temporal_link_movielens_cpu.py) (#8820) Distributed training on XPU device (examples/multi_gpu/distributed_sampling_xpu.py) (#8032) Multi-node multi-GPU training on ogbn-papers100M (examples...
Most GNN modules can now operate onbipartite graphs(and some of them can also operate ondifferent feature dimensionalitiesfor source and target nodes), useful for neighbor sampling or heterogeneous graphs: conv = SAGEConv(in_channels=(32, 64), out_channels=64) ...
ModelHomogeneousHeterogeneousNode Features GraphSage✔️✔️ GAT✔️✔️ Metapath2Vec✔️ DMGI✔️✔️ Quickstart: Downstream Tasks In addition, the library also provides various low-code helper methods to carry out number of downstream tasks such as visualisation, similarity sear...