Repository for benchmarking graph neural networks
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Updated
Jun 22, 2023 - Jupyter Notebook
Repository for benchmarking graph neural networks
Graph Neural Networks with Keras and Tensorflow 2.
Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.
Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)
Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022
Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch
Locally Private Graph Neural Networks (ACM CCS 2021)
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation (USENIX Security '23)
Android Malware Detection with Graph Convolutional Networks using Function Call Graph and its Derivatives.
An unofficial implementation of Graph Transformer (Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification) - IJCAI 2021
slientruss3d : Python for stable truss analysis and optimization tool
NLP - Semantic Role Labeling using GCN, Bert and Biaffine Attention Layer. Developed in Pytorch
An attempt at demystifying graph deep learning
Tumor2Graph: a novel Overall-Tumor-Profile-derived virtual graph deep learning for predicting tumor typing and subtyping.
ProGAP: Progressive Graph Neural Networks with Differential Privacy Guarantees (WSDM 2024)
Antibiotic discovery using graph deep learning, with Chemprop.
A repo for baseline of graph pooling.
Graph Deep Learning Course Presentation - Action and Emotion Recognition by Graph Convolutional Network(GCN)
Deep Learning with Graph Representation of Bio-Molecules to estimate physical Properties
Final assignment of EE226 course in SJTU by Group 12
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