srch

29.12.2021 · Issues. Pull requests. [NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen. self-supervised-learning pre-training graph-neural …

graph-neural-network,Awesome papers about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs). 将深度学习技术(图神经网络 ...

09.11.2019 · [ICLR 2017]Semi-Supervised Classification with Graph Convolutional Networks 【Graph Neural Network】GCN：算法原理，实现和应用: GraphSAGE [NIPS 2017]Inductive representation learning on large graphs 【Graph Neural Network】GraphSAGE：算法原理，实现和应用: GAT [ICLR 2018]Graph Attention Nerworks

05.06.2021 · Graph Neural Networks with Generated Parameters for Relation Extraction. ACL 2019. paper. Hao Zhu, Yankai Lin, Zhiyuan Liu, Jie Fu, Tat-seng Chua, Maosong Sun. Generating Logical Forms from Graph Representations of Text and Entities. ACL 2019. paper. Peter Shaw, Philip Massey, Angelica Chen, Francesco Piccinno, Yasemin Altun.

Spektral: Graph Neural Networks in TensorFlow 2 and Keras. ... The source code of the project is available on Github. Read the documentation here.

The field of graph neural networks (GNNs) has seen rapid and incredible strides over the recent years. Graph neural networks, also known as deep learning on graphs, graph representation learning, or geometric deep learning have become one of the fastest-growing research topics in machine learning, especially deep learning.

Graph Neural Networks Libraries. Deep Graph Library (DGL). A Python package that interfaces between existing tensor libraries and data being expressed as graphs ...

Python package built to ease deep learning on graph, on top of existing DL frameworks. deep-learning graph-neural-networks. Updated 2 hours ago; Python ...

Graph Neural Network Library for PyTorch. Contribute to pyg-team/pytorch_geometric development by creating an account on GitHub.