zhiqiangzhongddu

AdamGNN

[TKDE] Multi-grained Semantics-aware Graph Neural Networks (https://arxiv.org/abs/2010.00238)

Awesome-Knowledge-augmented-GML-for-Drug-Discovery

A collection of resources related with Knowledge-augmented Graph Machine Learning for Drug Discovery.

Data-Science-Interview-Questions-and-Answers-General-

Data Science Questions and Answers (General) for beginner

EvolMPNN

HC-GNN

[DMKD-ECMLPKDD] Hierarchical Message-Passing Graph Neural Networks (https://arxiv.org/abs/2009.03717)

KDD2023_KaGML_DrugDiscovery_Tutorial

Materials for KDD2023 tutorial: Knowledge-augmented Graph Machine Learning for Drug Discovery: from Precision to Interpretability

LLMaMol

PM-HGNN

[DMKD-ECMLPKDD] Personalised Meta-path Generation for Heterogeneous Graph Neural Networks (https://arxiv.org/abs/2010.13735)

SELENE

[TMLR] Unsupervised Network Embedding Beyond Homophily (https://arxiv.org/abs/2203.10866) Resources

TMLR-CLP

[TMLR] Simplifying Node Classification on Heterophilous Graphs with Compatible Label Propagation (https://arxiv.org/abs/2205.09389)

zhiqiangzhongddu/Data-Science-Interview-Questions-and-Answers-General-

Data Science Questions and Answers (General) for beginner

zhiqiangzhongddu/Awesome-Knowledge-augmented-GML-for-Drug-Discovery

A collection of resources related with Knowledge-augmented Graph Machine Learning for Drug Discovery.

zhiqiangzhongddu/KDD2023_KaGML_DrugDiscovery_Tutorial

Materials for KDD2023 tutorial: Knowledge-augmented Graph Machine Learning for Drug Discovery: from Precision to Interpretability

zhiqiangzhongddu/HC-GNN

[DMKD-ECMLPKDD] Hierarchical Message-Passing Graph Neural Networks (https://arxiv.org/abs/2009.03717)

zhiqiangzhongddu/SELENE

[TMLR] Unsupervised Network Embedding Beyond Homophily (https://arxiv.org/abs/2203.10866) Resources

zhiqiangzhongddu/PM-HGNN

[DMKD-ECMLPKDD] Personalised Meta-path Generation for Heterogeneous Graph Neural Networks (https://arxiv.org/abs/2010.13735)

zhiqiangzhongddu/LLMaMol

zhiqiangzhongddu/AdamGNN

[TKDE] Multi-grained Semantics-aware Graph Neural Networks (https://arxiv.org/abs/2010.00238)

zhiqiangzhongddu/EvolMPNN

zhiqiangzhongddu/TMLR-CLP

[TMLR] Simplifying Node Classification on Heterophilous Graphs with Compatible Label Propagation (https://arxiv.org/abs/2205.09389)

zhiqiangzhongddu/NeuLP

[WISE20] NeuLP: An End-to-end Deep-learning Model for Link Prediction (https://dl.acm.org/doi/abs/10.1007/978-3-030-62005-9_8)

zhiqiangzhongddu/RL-HGNN

zhiqiangzhongddu/Arion-Caterpillar-Tube-Pricing

zhiqiangzhongddu/easy-bib-python3

zhiqiangzhongddu/Filtre-particulaire

zhiqiangzhongddu/academicpages.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

zhiqiangzhongddu/GaI-Image

zhiqiangzhongddu/GearNet

GearNet and Geometric Pretraining Methods for Protein Structure Representation Learning, ICLR'2023 (https://arxiv.org/abs/2203.06125)

zhiqiangzhongddu/GNNPapers

Must-read papers on graph neural networks (GNN)

zhiqiangzhongddu/H2GCN

Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)

zhiqiangzhongddu/LaMolT5

zhiqiangzhongddu/Learning-Sleep-Quality-from-Daily-Logs

Learning Sleep Quality from Daily Logs in Tensorflow.

zhiqiangzhongddu/LLMCorr

zhiqiangzhongddu/NodeFormer

The official implementation of NeurIPS22 spotlight paper "NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification"

zhiqiangzhongddu/PEER_Benchmark

PEER Benchmark, appear at NeurIPS 2022 Dataset and Benchmark Track (https://arxiv.org/abs/2206.02096)

zhiqiangzhongddu/Porto-Seguro-s-Safe-Driver-Prediction

zhiqiangzhongddu/PosthocGnnExplainerRobust

[LOG] On the Robustness of Post-hoc GNN Explainers to Label Noise (https://arxiv.org/pdf/2309.01706)

zhiqiangzhongddu/pytorch_geometric

Graph Neural Network Library for PyTorch

zhiqiangzhongddu/Pytorch_tutorial

tutorial docs for Pytorch

zhiqiangzhongddu/TF-IDF