trustagi-lab Goto Github PK
Name: Trustworthy AGI (TrustAGI) Lab
Type: Organization
Bio: TrustAGI Lab, Led by Shirui Pan
Location: Melbourne, Australia
Name: Trustworthy AGI (TrustAGI) Lab
Type: Organization
Bio: TrustAGI Lab, Led by Shirui Pan
Location: Melbourne, Australia
[CIKM 2021] A PyTorch implementation of "ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning".
This is a TensorFlow implementation of the Adversarially Regularized Graph Autoencoder(ARGA) model as described in our paper: Pan, S., Hu, R., Long, G., Jiang, J., Yao, L., & Zhang, C. (2018). Adversarially Regularized Graph Autoencoder for Graph Embedding, [https://www.ijcai.org/proceedings/2018/0362.pdf].
Pytorch implementation of WWW'23:"Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs"
Awesome resources related to GNNs for Time Series Analysis (GNN4TS) 🔥 https://arxiv.org/abs/2307.03759
Paper Lists for Graph Neural Networks
Awesome papers about unifying LLMs and KGs
A professional list on Large (Language) Models and Foundation Models (LLM, LM, FM) for Time Series, Spatiotemporal, and Event Data.
BANE: Binarized Attributed Network Embedding - ICDM2018
[TNNLS] Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning
A PyTorch implementation of "GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection", WSDM-23
This repository summarises the open source codes of our group
Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination"
A Repository of Benchmark Graph Datasets for Graph Classification (31 Graph Datasets In Total).
A PyTorch implementation of "Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating", AAAI-23
Official code implementation for WSDM 23 paper Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs.
[IJCAI 2021] A PyTorch implementation of "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning".
Implementation of the CIKM-17 paper “MGAE: Marginalized Graph Autoencoder for Graph Clustering”
Pytorch implementation of ICDM'22 "Multi-Relational Graph Neural Architecture Search with Fine-grained Message Passing"
Joint Structure Feature Exploration and Regularization for Multi-Task Graph Classification
[TKDE 2022] The official PyTorch implementation of the paper "Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs".
[NIPS 2022] The official PyTorch implementation of "Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs"
OpenWGL: Open-World Graph Learning, ICDM-2020
PSICHIC (pronounced Psychic) - PhySIcoCHemICal graph neural network for learning protein-ligand interaction fingerprints from sequence data
Official code for RawNP (ECML-PKDD 2023)
Official Implementation of "Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning"
[WWW'22] Towards Unsupervised Deep Graph Structure Learning
Tri-Party Deep Network Representation, IJCAI-16
Python implementation of "Unsupervised Domain Adaptive Graph Convolutional Networks", WWW-20.
The open source code for ICDM2022 paper "Unifying Graph Contrastive Learning with Flexible Contextual Scopes"
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