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Composing Graph Theory and Deep Neural Networks to Evaluate SEU Type Soft Error Effects., , , , and . MECO, page 1-5. IEEE, (2020)Functional Failure Rate Due to Single-Event Transients in Clock Distribution Networks., , , and . CoRR, (2020)On the Estimation of Complex Circuits Functional Failure Rate by Machine Learning Techniques., , , , and . CoRR, (2020)Enabling Cross-Layer Reliability and Functional Safety Assessment Through ML-Based Compact Models., , , and . IOLTS, page 1-6. IEEE, (2020)A Novel Error Rate Estimation Approach forUltraScale+ SRAM-based FPGAs., , , , , , , , and . AHS, page 120-126. IEEE, (2018)On the Estimation of Complex Circuits Functional Failure Rate by Machine Learning Techniques., , , , and . DSN (Supplements), page 35-41. IEEE, (2019)Modeling Gate-Level Abstraction Hierarchy Using Graph Convolutional Neural Networks to Predict Functional De-Rating Factors., , , , and . AHS, page 72-78. IEEE, (2019)The Validation of Graph Model-Based, Gate Level Low-Dimensional Feature Data for Machine Learning Applications., , , , and . NORCAS, page 1-7. IEEE, (2019)Functional Failure Rate Due to Single-Event Transients in Clock Distribution Networks., , , and . DTIS, page 1-6. IEEE, (2019)Machine Learning to Tackle the Challenges of Transient and Soft Errors in Complex Circuits., , , , and . CoRR, (2020)