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Resilience-Performance Tradeoff Analysis of a Deep Neural Network Accelerator., , , , , and . DDECS, page 181-186. IEEE, (2023)AdequateDL: Approximating Deep Learning Accelerators., , , , , , and . DDECS, page 37-40. IEEE, (2021)Selective Hardening of Critical Neurons in Deep Neural Networks., , , , , and . DDECS, page 136-141. IEEE, (2022)Emerging Computing Devices: Challenges and Opportunities for Test and Reliability*., , , , , , , , , and 2 other author(s). ETS, page 1-10. IEEE, (2021)Assertion-aware approximate computing design exploration on behavioral models., , , , , and . LATS, page 1-6. IEEE, (2022)Testing approximate digital circuits: Challenges and opportunities., , , , and . LATS, page 1-6. IEEE, (2018)Reliability of computing systems: From flip flops to variables., , , , and . IOLTS, page 196-198. IEEE, (2017)Computing reliability: On the differences between software testing and software fault injection techniques., , , , , and . Microprocess. Microsystems, (2017)Sensitivity Analysis and Compression Opportunities in DNNs Using Weight Sharing., , , and . DDECS, page 1-6. IEEE, (2020)A study of path delay variations in the presence of uncorrelated power and ground supply noise., , , , , and . DDECS, page 189-194. IEEE Computer Society, (2011)