Topic: dgl Goto Github
Some thing interesting about dgl
Some thing interesting about dgl
dgl,Protein Graph Library
User: a-r-j
Home Page: https://graphein.ai/
dgl,Multilabel Aspect Prediction using Graph Convolutional Networks
User: abhinavg97
dgl,Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on Deep Graph Library (DGL)
User: acbull
dgl,Financial Product Recommendation With Graph ML
Organization: awslabs
dgl,High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.
Organization: awslabs
Home Page: https://dglke.dgl.ai/doc/
dgl,Python package for graph neural networks in chemistry and biology
Organization: awslabs
dgl,An end-to-end blueprint architecture for real-time fraud detection(leveraging graph database Amazon Neptune) using Amazon SageMaker and Deep Graph Library (DGL) to construct a heterogeneous graph from tabular data and train a Graph Neural Network(GNN) model to detect fraudulent transactions in the IEEE-CIS dataset.
Organization: awslabs
Home Page: https://awslabs.github.io/realtime-fraud-detection-with-gnn-on-dgl/
dgl,This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.
Organization: bupt-gamma
dgl,Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network
Organization: bupt-gamma
dgl,This Repository includes DGL tutorials and various information related to graph neural networks.
User: ceo21ckim
dgl,[PAKDD 2021] Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning
User: cmavro
Home Page: https://arxiv.org/abs/2009.06946
dgl,Diffpool implementation for GDLMA SoSe22 @ TUM
User: d-stoll
dgl,A tool for generating PDEs ground truth datasets from ARCSim, FEniCS and SU2
Organization: diffeqml
dgl,Visualization tool for Graph Neural Networks
Organization: dmlc
dgl,Source code for EMNLP 2020 paper: Double Graph Based Reasoning for Document-level Relation Extraction
User: dreaminvoker
dgl,GraphGallery is a gallery for benchmarking Graph Neural Networks, From InplusLab.
User: edisonleeeee
dgl,[CIKM 2023] GUARD: Graph Universal Adversarial Defense
User: edisonleeeee
dgl,A knowledge graph and a set of tools for drug repurposing
Organization: gnn4dr
dgl,Repository for benchmarking graph neural networks
Organization: graphdeeplearning
Home Page: https://arxiv.org/abs/2003.00982
dgl,Open MatSci ML Toolkit is a framework for prototyping and scaling out deep learning models for materials discovery supporting widely used materials science datasets, and built on top of PyTorch Lightning, the Deep Graph Library, and PyTorch Geometric.
Organization: intellabs
dgl,Set of PyTorch modules for developing and evaluating different algorithms for embedding trees.
Organization: jetbrains-research
dgl,PyTorch-Direct code on top of PyTorch-1.8.0nightly (e152ca5) for Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture (accepted by PVLDB)
User: k-wu
Home Page: https://arxiv.org/abs/2103.03330
dgl,2021MXAP-DGL rank2
User: langgege-cqu
dgl,Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric
User: lukecavabarrett
Home Page: https://arxiv.org/abs/2004.05718
dgl,Predict CS Paper's Subject Area Using Graph Neural Networks
User: nhatsmrt
dgl,Senior Capstone Project: Graph-Based Product Recommendation
User: nhtsai
Home Page: https://nhtsai.github.io/graph-rec/
dgl,Bag of Tricks for Graph Neural Networks.
User: sangyx
Home Page: https://sangyx.com/gtrick/
dgl,Implementation of Directional Graph Networks in PyTorch and DGL
User: saro00
Home Page: https://arxiv.org/abs/2010.02863
dgl,DGL implementation of GNN-CCA: Graph Neural Networks for Cross-Camera Data Association [arXiv:2201.06311]
User: shawnh2
dgl,Reimplementation of Graph Autoencoder by Kipf & Welling with DGL.
User: shionhonda
Home Page: https://arxiv.org/abs/1611.07308
dgl,DGL中文文档。This is the Chinese manual of the graph neural network library DGL, currently contains the User Guide.
User: taishan1994
dgl,Android Malware Detection with Graph Convolutional Networks using Function Call Graph and its Derivatives.
User: vinayakakv
dgl,Colab implementation for Fraud Detection in Graph Neural Networks, based on Deep Graph Library (DGL) and PyTorch backend.
User: waittim
dgl,DGL implementation of EGES
User: wang-yu-qing
dgl,NebulaGraph DGL(Deep Graph Library) Integration Package. (WIP)
User: wey-gu
dgl,An example project for training a GraphSAGE Model, and setup a Real-time Fraud Detection Web Service(Frontend and Backend) with NebulaGraph Database and DGL.
User: wey-gu
Home Page: https://siwei.io/fraud-detection-with-nebulagraph/
dgl,yelp-frauddetection dataset in CSV for NebulaGraph
User: wey-gu
dgl,Course project of SJTU CS3319: Foundations of Data Science, 2023 spring
User: wzever
dgl,A DGL implementation of "Graph Neural Networks with convolutional ARMA filters". (PAMI 2021)
User: xnuohz
dgl,A DGL implementation of "Combining Label Propagation and Simple Models Out-performs Graph Neural Networks" (ICLR 2021).
User: xnuohz
dgl,A DGL implementation of "DeeperGCN: All You Need to Train Deeper GCNs".
User: xnuohz
dgl,Various GNN implementation using DGL library
User: yoongi0428
dgl,MAXP 命题赛 任务一:基于DGL的图机器学习任务。队伍:Graph@ICT,🥉rank6。https://www.biendata.xyz/competition/maxp_dgl/
User: ytchx1999
dgl,Implementation of "Denoise Pretraining on Non-equilibrium Molecular Conformations for Accurate and Transferable Neural Potentials" in PyTorch.
User: yuyangw
dgl,Course: Graph Machine Learning focuses on the application of machine learning algorithms on graph-structured data. Some of the key topics that are covered in the course include graph representation learning and graph neural networks, algorithms for the world wide web, reasoning over knowledge graphs, and social network analysis.
User: zahta
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