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awesome-graph-attack-papers

Adversarial attacks and defenses on Graph Neural Networks.

awesome-graph-transformer

Papers about graph transformers.

being-robust-can-be-practical

Being Robust (in High Dimensions) Can Be Practical

clrs

digraph_transformer-fork

graph-adversarial-learning-literature

A curated list of adversarial attacks and defenses papers on graph-structured data.

grb

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

jaxline

jsts

JavaScript Topology Suite

kafka

A high-throughput, distributed, publish-subscribe messaging system

models

Models and examples built with TensorFlow

pix2pixhd

Synthesizing and manipulating 2048x1024 images with conditional GANs

posterior-network

Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)

pprgo_pytorch

PPRGo model in PyTorch, as proposed in "Scaling Graph Neural Networks with Approximate PageRank" (KDD 2020)

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

pytorch_geometric

Graph Neural Network Library for PyTorch

releasing-research-code

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

reliable_gnn_via_robust_aggregation

This repository contains the official implementation of the paper "Reliable Graph Neural Networks via Robust Aggregation" (NeurIPS, 2020).

robustness_of_gnns_at_scale

This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).

s2gnn

travelling-salesman-electric-vehicles

Solves the traveling salesman problem for a specialised electric car profile and compares the results with a regular profile