Giter Club home page Giter Club logo

mgae's Introduction

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)

mgae's People

Contributors

faketibbers avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar

mgae's Issues

Thank you for sharing your work!

Hi,

Your work is great, and it may be useful for my research, thank yo for sharing!
Is it possible to share the code you use the plot the results? I would like to see the data as you show in Figure 5 of the paper, the 2D visualization of the various layers.

Thank you!

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.