Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch
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Updated
Aug 13, 2020 - Python
Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch
NLP - Semantic Role Labeling using GCN, Bert and Biaffine Attention Layer. Developed in Pytorch
Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.
Android Malware Detection with Graph Convolutional Networks using Function Call Graph and its Derivatives.
Tumor2Graph: a novel Overall-Tumor-Profile-derived virtual graph deep learning for predicting tumor typing and subtyping.
An attempt at demystifying graph deep learning
Final assignment of EE226 course in SJTU by Group 12
Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022
Antibiotic discovery using graph deep learning, with Chemprop.
Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)
Non markovian extension to the graph edit network model proposed by Paassen et al.
A repo for baseline of graph pooling.
Deep Learning with Graph Representation of Bio-Molecules to estimate physical Properties
slientruss3d : Python for stable truss analysis and optimization tool
Repository for benchmarking graph neural networks
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation (USENIX Security '23)
Locally Private Graph Neural Networks (ACM CCS 2021)
ProGAP: Progressive Graph Neural Networks with Differential Privacy Guarantees (WSDM 2024)
Graph Neural Networks with Keras and Tensorflow 2.
An unofficial implementation of Graph Transformer (Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification) - IJCAI 2021
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