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Scalable Machine Learning to Estimate the Impact of Aging on Circuits Under Workload Dependency., and . IEEE Trans. Circuits Syst. I Regul. Pap., 69 (5): 2142-2155 (2022)Variability-Aware Approximate Circuit Synthesis via Genetic Optimization., , , , , and . IEEE Trans. Circuits Syst. I Regul. Pap., 69 (10): 4141-4153 (2022)On Extracting Reliability Information from Speed Binning., , , and . ETS, page 1-4. IEEE, (2022)Machine Learning for On-the-Fly Reliability-Aware Cell Library Characterization., and . IEEE Trans. Circuits Syst. I Regul. Pap., 68 (6): 2569-2579 (2021)Intelligent Methods for Test and Reliability., , , , , , , , , and 25 other author(s). DATE, page 969-974. IEEE, (2022)ML to the Rescue: Reliability Estimation from Self-Heating and Aging in Transistors All the Way up Processors., and . ASP-DAC, page 76-82. ACM, (2023)Modeling Emerging Technologies using Machine Learning: Challenges and Opportunities., , , , and . ICCAD, page 15:1-15:9. IEEE, (2020)GNN4REL: Graph Neural Networks for Predicting Circuit Reliability Degradation., , , , and . CoRR, (2022)Robust Resistive Open Defect Identification Using Machine Learning with Efficient Feature Selection., , , , and . DATE, page 1-2. IEEE, (2023)Design Automation for Cryogenic CMOS Circuits., , , , , , , and . DAC, page 1-6. IEEE, (2023)