Instruction-aware Learning-based Timing Error Models through Significance-driven Approximations. - Styliani Tompazi; Ioannis Tsiokanos; Jesús Martínez del Rincón; Lev Mukhanov; Georgios Karakonstantis (ICCD, 2022)

AI-based Timing Error Modelling: A Case Study on a Pipelined Floating-point Core. - Styliani Tompazi; Georgios Karakonstantis (ARITH, 2023)

A Compressed and Accurate Sparse Deep Learning-based Workload-Aware Timing Error Model. - Styliani Tompazi; Georgios Karakonstantis (ICCD, 2023)

Microarchitecture-Aware Timing Error Prediction via Deep Neural Networks. - Styliani Tompazi; Georgios Karakonstantis (IOLTS, 2023)

Estimating Code Vulnerability to Timing Errors Via Microarchitecture-Aware Machine Learning. - Styliani Tompazi; Ioannis Tsiokanos; Jesús Martínez del Rincón; Georgios Karakonstantis (IEEE Des. Test, 2023)

ARETE: Accurate Error Assessment via Machine Learning-Guided Dynamic-Timing Analysis. - Ioannis Tsiokanos; Styliani Tompazi; Giorgis Georgakoudis; Lev Mukhanov; Georgios Karakonstantis (IEEE Trans. Computers, 2023)