188 Open source projects that are alternatives of or similar to SimP-GCN

Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"

Python toolbox to evaluate graph vulnerability and robustness (CIKM 2021)

A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).

links to conference publications in graph-based deep learning

Summary of open source code for deep learning models in the field of traffic prediction

Papers about explainability of GNNs

Code and resources on scalable and efficient Graph Neural Networks

Graph Neural Network Library for PyTorch

Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph Machine Learning.

A 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).

A reading list for deep graph learning acceleration.

An Algorithm to Quantify Robustness of Recurrent Neural Networks

Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"

ProteinGCN: Protein model quality assessment using Graph Convolutional Networks

Representation Learning on Graphs with Jumping Knowledge Networks

StellarGraph - Machine Learning on Graphs

A distributed graph deep learning framework.

Source code and dataset for the CCKS201 paper "On Robustness and Bias Analysis of BERT-based Relation Extraction"

An index of recommendation algorithms that are based on Graph Neural Networks.

Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper

Square Attack: a query-efficient black-box adversarial attack via random search [ECCV 2020]

Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".

[CVPR 2022] S-attack library. Official implementation of two papers "Vehicle trajectory prediction works, but not everywhere" and "Are socially-aware trajectory prediction models really socially-aware?".

Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".

Code for the AAAI 2022 publication "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"

Tutorials for Machine Learning on Graphs

Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning (authors' MXNet implementation for the TACL19 paper)

[NeurIPS 2021]: Are Transformers More Robust Than CNNs? (Pytorch implementation & checkpoints)

Visualization tool for Graph Neural Networks

An alternative implementation of Recursive Feature and Role Extraction (KDD11 & KDD12)

A collection of ML related stuff including notebooks, codes and a curated list of various useful resources such as books and softwares. Almost everything mentioned here is free (as speech not free food) or open-source.

Code for the CHAMPS Predicting Molecular Properties Kaggle competition

(ICML 2022) Official PyTorch implementation of “Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness”.

Overlapping community detection in Large-Scale Networks using BigCLAM model build on Apache Spark

A tutorial & minimal example (8min on CPU) for Graph Convolutional Networks for Text Classification. AAAI 2019

Demo of RouteNet in ACM SIGCOMM'19

GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification

Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)

A collection of important graph embedding, classification and representation learning papers with implementations.

Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)

PyTorch Implementation of GraphTSNE, ICLR’19

Code and data for ECML-PKDD paper "Social Influence Attentive Neural Network for Friend-Enhanced Recommendation"

Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders (IJCAI 2018)

No description or website provided.

Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks

Code for Graph Convolutional Matrix Factorization for Bipartite Edge Prediction

Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.

A Context-aware Visual Attention-based training pipeline for Object Detection from a Webpage screenshot!

Disentagnled Graph Collaborative Filtering, SIGIR2020

Tensorflow Implementation of the paper "Topology Adaptive Graph Convolutional Networks" (Du et al., 2017)

The implement of GNN based on Pytorch

Recentrifuge: robust comparative analysis and contamination removal for metagenomics

GraphNVP: An Invertible Flow Model for Generating Molecular Graphs

A Reproducible Workflow for Structural and Functional Connectome Ensemble Learning

Material for the EPFL master course "A Network Tour of Data Science", edition 2019.

odr.chalmers.se/handle/20.500.12380/256629?locale=en

A graph-based deep learning framework for life science

ACL 2018: Dating Documents using Graph Convolution Networks

Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation, AAAI 2020

Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits