Bags of Tricks in OGB (node classification) with GCNs.
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Updated
Aug 11, 2021 - Python
Bags of Tricks in OGB (node classification) with GCNs.
Tools for querying, visualizing, and modeling network graphs on the Helium blockchain.
Project for Deep Learning And Applied AI course at the University of "La Sapienza" in Master in Computer Science A.A. 2021/2022
g2-MLP: State-of-the-Art Model for Node Classification on Graphs (PPI Dataset)
In this repo I have implement different applications of GNN which covers Node Level, Edge level, Graph level tasks with different GNN variants such as GCN, GAT, Graph SAGE
An introduction to graph neural networks with pytorch
Code repo for the paper "AIO-P: Expanding Neural Performance Predictors Beyond Image Classification", accepted to AAAI-23.
Kaggle competition (2023). Predict neutrino particle direction with Deep Graph Neural Networks.
This project optimizes a Graph Convolutional Network (GCN) model with Optuna to predict COVID-19 cases in various regions, incorporating additional features alongside historical data for improved accuracy.
Experimentation on PRODIGY framework
Your PyTorch AI Factory - Flash enables you to easily configure and run complex AI recipes for over 15 tasks across 7 data domains
Bag of Tricks for Graph Neural Networks.
Code repo for the paper "GENNAPE: Towards Generalized Neural Architecture Performance Estimators", accepted to AAAI-23.
PyTorch code for an effective way of making a Molecular Graph Dataset in Torch Geometric involving a pair of graphs from chemical SMILE strings
Datasets for modeling transformations in data.
Torch geometric compatible node embedders
GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.
This repository is a brief tutorial about how Graph convolutional networks and message passing networks work with example code demonstration using pytorch and torch_geometric
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