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Graph Self-Supervised Learning With Application to Brain Networks Analysis.

, , , , , , and . IEEE J. Biomed. Health Informatics, 27 (8): 4154-4165 (August 2023)

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ODD and Behavior Based Scenario Generation for Automated Driving Systems., , , , , and . IEEE Access, (2024)BrainTGL: A dynamic graph representation learning model for brain network analysis., , , , , , and . Comput. Biol. Medicine, (February 2023)Writing Accessible and Correct Test Scenarios for Automated Driving Systems., , , , and . SMC, page 1356-1363. IEEE, (2022)A Novel Skill Model Supporting Complex and Reliable Interactions between Users, VPA and External Services., , , and . EDGE, page 133-142. IEEE, (2022)Efficient target control of complex networks based on preferential matching., , and . CoRR, (2016)Understanding security failures of multi-factor authentication schemes for multi-server environments., , , and . Comput. Secur., (2020)Response to: Significance and stability of deep learning-based identification of subtypes within major psychiatric disorders. Molecular Psychiatry (2022)., , and . CoRR, (2022)Validating Simulation Environments for Automated Driving Systems Using 3D Object Comparison Metric., , , , , , , and . IV, page 860-866. IEEE, (2022)A Novel Scenario-Based Testing Approach for Cooperative-Automated Driving Systems., , , , , , and . SMC, page 3487-3494. IEEE, (2023)Temporal Weighted Heterogeneous Multigraph Embedding for Ethereum Phishing Scams Detection., , , , and . CSCWD, page 1208-1213. IEEE, (2023)