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Highlights
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Stars
Learning to Group Auxiliary Datasets for Molecule, NeurIPS2023
This repository contains implementations and illustrative code to accompany DeepMind publications
C++/CUDA implementation of the most popular hyperbolic and parabolic PDE solvers
Python library assists deep learning on graphs
Combining relational context and relational paths for knowledge graph completion
Neural relational inference for interacting systems - pytorch
Compute graph embeddings via Anonymous Walk Embeddings
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
pytorch implementation of structure2vec (https://arxiv.org/abs/1603.05629)
Graph Neural Network Library for PyTorch
PyTorch Extension Library of Optimized Graph Cluster Algorithms
Representation learning on large graphs using stochastic graph convolutions.
An Open Source Machine Learning Framework for Everyone
Simple reference implementation of GraphSAGE.
Training computational graph on top of structured data (string, graph, etc)
Tools for accessing/processing Reddit data and constructing networks based on this data. (Not an API crawler.)
GoogleTest - Google Testing and Mocking Framework