zhh0998

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2019-GraphNeuralNetworksPaperList

Graph Neural Networks Paper List of 2019 Conferences

AdvT4NE_WWW2019

Adversarial Training Methods for Network Embedding, WWW2019.

AttentionWalk

A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).

Awesome-Dynamic-Graph-Representaiton-Learning-Papers

A collection of dynamic graph representation learning papers

awesome-network-embedding

A curated list of network embedding techniques.

dynamic-graph-embedding-method

dynamic graph/network embedding/representation methods

Graph

NetWalk

Implementation of the Paper(KDD'18) NetWalk: A Flexible Deep Embedding Approach for Anomaly Detection in Dynamic Networks.

OpenHINE

An Open-Source Toolkit for Heterogeneous Information Network Embedding (HINE)

zhh0998/dynamic-graph-embedding-method

dynamic graph/network embedding/representation methods

zhh0998/OpenHINE

An Open-Source Toolkit for Heterogeneous Information Network Embedding (HINE)

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zhh0998/Awesome-GNN-Recommendation

Graph Neural Network

zhh0998/awesome-graph-classification

A collection of important graph embedding, classification and representation learning papers with implementations.

zhh0998/CS-GNN

Measuring and Improving the Use of Graph Information in Graph Neural Networks

zhh0998/dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

zhh0998/Dynamic-graph-dataset

Dynamic graph/network dataset for dynamic graph/network embedding/representation

zhh0998/GloDyNE

GloDyNE: Global Topology Preserving Dynamic Network Embedding

zhh0998/GNN4NLP-Papers

A list of recent papers about Graph Neural Network methods applied in NLP areas.

zhh0998/GNNs-for-NLP

Graph Neural Networks for Natural Language Processing tutorial at EMNLP 2019 and CODS-COMAD 2020

zhh0998/graph-based-deep-learning-literature

links to conference publications in graph-based deep learning

zhh0998/graph4nlp_literature

This repo is to provide a list of literature regarding Deep Learning on Graphs for NLP

zhh0998/Graph_Transformer_Networks

Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)

zhh0998/HGSL

Source code of AAAI21-Heterogeneous Graph Structure Learning for Graph Neural Networks

zhh0998/HierTCN

Hierarchical Temporal Convolutional Networks for Dynamic Recommender Systems

zhh0998/HIN-Datasets-for-Recommendation-and-Network-Embedding

Heterogeneous Information Network Datasets for Recommendation and Network Embedding

zhh0998/KRLPapers

Must-read papers on knowledge representation learning (KRL) / knowledge embedding (KE)

zhh0998/NetRA

Code for "Learning Deep Network Representations with Adversarially Regularized Autoencoders."

zhh0998/NeuralNetworkPointProcess

code for "Fully Neural Network based Model for General Temporal Point Processes"

zhh0998/NREPapers

Must-read papers on neural relation extraction (NRE)

zhh0998/nsfc

国家自然科学基金查询

zhh0998/point-process-nets

Point processes backed by neural net intensity models

zhh0998/PostgraduateEnrollementCrawller

硕士专业目录爬虫(Kotlin+JSoup+myBatis+mySQL)

zhh0998/py2so

:snake: py2so is tool to change the .py to .so, you can use it to hide the source code of py

zhh0998/pyHGT

Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric

zhh0998/PyTorch-GAN

PyTorch implementations of Generative Adversarial Networks.

zhh0998/Representation-Learning-on-Heterogeneous-Graph

Representation-Learning-on-Heterogeneous-Graph

zhh0998/TextGAN-PyTorch

TextGAN is a PyTorch framework for Generative Adversarial Networks (GANs) based text generation models.

zhh0998/wechat-chatgpt