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Found 3 papers, 1 papers with code
GAETS: A Graph Autoencoder Time Series Approach Towards Battery Parameter Estimation
In this paper we employ Graph Neural Networks for battery parameter estimation, we introduce a unique graph autoencoder time series estimation approach.
Data Considerations in Graph Representation Learning for Supply Chain Networks
It is anticipated that our method will be directly applicable to businesses wishing to sever links with nefarious entities and mitigate risk of supply failure.
On Graph Neural Network Ensembles for Large-Scale Molecular Property Prediction
In order to advance large-scale graph machine learning, the Open Graph Benchmark Large Scale Challenge (OGB-LSC) was proposed at the KDD Cup 2021.
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