SEARCH · Search NASA
Results for “Graph Neural Network”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Observation of a rare beta decay of the charmed baryon with a Graph Neural Network
Not provided.
Predicting magnetic properties of van der Waals magnets using graph neural networks
Not Available
A Graph Neural Network for Reconstruction of LArTPC Detector Data
Explore the source record for details and available documents.
Enabling Real-Time Communications in Multi-Agent Systems: A Graph Neural Network Based Approach
Explore the source record for details and available documents.
Graph Neural Networks for 3D Geometry-Agnostic Predictions of Material Behavior
Explore the source record for details and available documents.
A New Bi-Partite Graph Representation of 3D Solids for Geometric Reasoning and Graph Neural Networks
Explore the source record for details and available documents.
Pattern Mining in Graphs via Graph Neural Networks (GNNs)
Explore the source record for details and available documents.
Anomaly Detection in the SBND Experiment Based on Graph Neural Networks
Traditional anomaly detection in SBND experiments require data reconstruction and manual supervision, and thus has the drawbacks of long detection time, being labour intensive and incapable of predicting potential future anomalies. Machine learning models, especially autoencoders, have been widely applied in anomaly detection, and developing an autoencoder for anomaly detection in SBND experiment is going to tremendously improve the efficiency and accuracy of the experiment. The autoencoder has the advantage of automation, efficiency, and can be used to predict future anomalies in the SBND experiment.
Direct prediction of quantum circuit outcome probabilities using physics-aware graph neural networks
Explore the source record for details and available documents.
Direct prediction of quantum circuit outcome probabilities using physics-aware graph neural networks
Explore the source record for details and available documents.
Graph Neural Network Models of Multiphase Flow from Boundary Integral Methods
Explore the source record for details and available documents.
Predicting the Functional State of Protein Kinases Using Interpretable Graph Neural Networks
Explore the source record for details and available documents.
Interpretable Graph Neural Networks for Predicting the Functional State of Protein Kinases
Explore the source record for details and available documents.
Predicting Stellar Masses of the First Galaxies Using Graph Neural Networks
Explore the source record for details and available documents.
Street-level temperature estimation using graph neural networks: Performance, feature embedding and interpretability
Explore the source record for details and available documents.
Predicting Lattice Vibrational Frequencies Using Deep Graph Neural Networks
Explore the source record for details and available documents.