Skip to content

This repository summarises the open source codes of our group

License

Notifications You must be signed in to change notification settings

TrustAGI-Lab/graph-deep-learning

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

24 Commits
 
 
 
 

Repository files navigation

graph-deep-learning

This page summarises the open source code of our group, mostly on graph learning & deep learning. More source code will be released as it is ready for publishing. You can visit your GRAND Lab page on Github for more details.

Graph Learning & Deep Learning

  • Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination (NeurIPS 2022)

  • Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs (NeurIPS 2022)

  • Unifying Graph Contrastive Learning with Flexible Contextual Scopes (ICDM 2022)

  • Towards Unsupervised Deep Graph Structure Learning (WWW 2022)

  • Beyond Low-pass Filtering: Graph Convolutional Networks with Automatic Filtering (TKDE 2022)

  • Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning (IJCAI 2021)

  • Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning (AAAI 2021)

  • ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning (CIKM 2021)

  • Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning (TNNLS 2021)

  • Open-World Graph Learning (ICDM 2020)

  • One-Shot Neural Architecture Search: Maximising Diversity to Overcome Catastrophic Forgetting (TPAMI 2020)

  • Graph Stochastic Neural Networks for Semi-supervised Learning (NeurIPS 2020)

  • Graph Geometry Interaction Learning (NeurIPS 2020)

  • Differentiable Neural Architecture Search in Equivalent Space with Exploration Enhancement (NeurIPS 2020)

  • Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks (KDD 2020)

  • Overcoming Multi-Model Forgetting in One-Shot NAS with Diversity Maximization (CVPR 2020)

  • Unsupervised Domain Adaptive Graph Convolutional Networks (WWW 2020)

  • GSSNN: Graph Smoothing Splines Neural Network (AAAI 2020)

  • Reinforcement Learning based Meta-path Discovery in Large-scale Heterogeneous Information Networks (AAAI 2020)

  • Relation Structure-Aware Heterogeneous Graph Neural Network (ICDM 2019)

  • Graph WaveNet for Deep Spatial-Temporal Graph Modeling (IJCAI 2019)

  • Adversarially regularized graph autoencoder for graph embedding (IJCAI 2018)

  • Binarized attributed network embedding (ICDM 2018)

  • MGAE: marginalized graph autoencoder for graph clustering (CIKM 2017)

  • Tri-party deep network representation (IJCAI 2016)

About

This repository summarises the open source codes of our group

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 3

  •  
  •  
  •