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Found 4 papers, 1 papers with code
G2A2: An Automated Graph Generator with Attributes and Anomalies
Many data-mining applications use dynamic attributed graphs to represent relational information; but due to security and privacy concerns, there is a dearth of available datasets that can be represented as dynamic attributed graphs.
A Deep-Learning Framework for Improving COVID-19 CT Image Quality and Diagnostic Accuracy
Our CT-based DL framework was developed to improve the testing speed and accuracy of COVID-19 (plus its variants) via a DL-based approach for CT image enhancement and classification.
SamBaS: Sampling-Based Stochastic Block Partitioning
We characterize how various graph parameters affect the speedup and result quality of community detection with SamBaS and quantify the trade-offs therein.
Extreme-Scale Programming Model for Quantum Acceleration within High Performance Computing
A novel approach to scale these applications with future heterogeneous HPC is to enhance conventional computing systems with quantum processor accelerators.
Quantum Physics
