autoupdate paper list

[IJCAI 2024] Papers about graph reduction including graph coarsening, graph condensation, graph sparsification, graph summarization, etc.

An infrastructure resilience web application to integrate graph neural networks (GNNs) for GIS visualization.

Python package built to ease deep learning on graph, on top of existing DL frameworks.

This is a master thesis project done by Ezgi Günbatar for Applied Data Science program at Utrecht University. The repository contains datasets and codebooks which are used in "The Role of Social Networks and Personal Characteristics in Shaping Fertility Intentions: A Multi-Method Machine Learning Perspective" study.

code for the paper "LayerDAG: A Layerwise Autoregressive Diffusion Model of Directed Acyclic Graphs"

Graph Neural Networks in Julia

[ICML 2023] Official implementation of "A randomized schur complement based graph augmentor"

sklearn for machine learning on graphs

A list of awesome GNN systems.

Graph Neural Network Library for PyTorch

Graph Convolution Network aided Sentiment Analysis with Dependencies utilisation

A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks

python library for atomistic machine learning

A PyG-based package of spectral GNNs with benchmark evaluations.

Official repository for the paper "Back to the Future: GNN-based NO2 Forecasting via Future Covariates", 2024

[ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"

🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

This repository contains code related to the automation of modeling efforts for the PINK project, focusing on training Graph Neural Networks (GNNs) for molecular property prediction from SMILES.