SuperGAT[ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision
GAugAAAI'21: Data Augmentation for Graph Neural Networks
BGCNA Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).
mdgradPytorch differentiable molecular dynamics
SiGATsource code for signed graph attention networks (ICANN2019) & SDGNN (AAAI2021)
pyg autoscaleImplementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch
Entity-Graph-VLNCode of the NeurIPS 2021 paper: Language and Visual Entity Relationship Graph for Agent Navigation
ASAPAAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
SubGNNSubgraph Neural Networks (NeurIPS 2020)
robust-gcnImplementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".
EgoCNNCode for "Distributed, Egocentric Representations of Graphs for Detecting Critical Structures" (ICML 2019)
visual-compatibilityContext-Aware Visual Compatibility Prediction (https://arxiv.org/abs/1902.03646)
AC-VRNNPyTorch code for CVIU paper "AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction"
SimP-GCNImplementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"
DCGCNDensely Connected Graph Convolutional Networks for Graph-to-Sequence Learning (authors' MXNet implementation for the TACL19 paper)
SIANCode and data for ECML-PKDD paper "Social Influence Attentive Neural Network for Friend-Enhanced Recommendation"
Pro-GNNImplementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"
PyNetsA Reproducible Workflow for Structural and Functional Connectome Ensemble Learning
kaggle-champsCode for the CHAMPS Predicting Molecular Properties Kaggle competition
GalaXCGalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification
SelfGNNA PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in The International Workshop on Self-Supervised Learning for the Web (SSL'21) @ the Web Conference 2021 (WWW'21).
ntds 2019Material for the EPFL master course "A Network Tour of Data Science", edition 2019.
GNNLens2Visualization tool for Graph Neural Networks
grbGraph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph Machine Learning.
RioGNNReinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks
3DInfomaxMaking self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.
LR-GCCFRevisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach, AAAI2020