Particle Monte Carlo modeling of single-event transient current and charge collection in integrated circuits. - Jean-Luc Autran; Maximilien Glorieux; Daniela Munteanu; Sylvain Clerc; Gilles Gasiot; Philippe Roche (Microelectron. Reliab., 2014)

A call for cross-layer and cross-domain reliability analysis and management. - Dan Alexandrescu; Adrian Evans; Enrico Costenaro; Maximilien Glorieux (IOLTS, 2015)

EDA support for functional safety - How static and dynamic failure analysis can improve productivity in the assessment of functional safety. - Dan Alexandrescu; Adrian Evans; Maximilien Glorieux; Issam Nofal (IOLTS, 2017)

A Novel Error Rate Estimation Approach forUltraScale+ SRAM-based FPGAs. - Luca Sterpone; Sarah Azimi; Ludovica Bozzoli; Boyang Du; Thomas Lange; Maximilien Glorieux; Dan Alexandrescu; Cesar Boatella Polo; David Merodio Codinachs (AHS, 2018)

Modeling Gate-Level Abstraction Hierarchy Using Graph Convolutional Neural Networks to Predict Functional De-Rating Factors. - Aneesh Balakrishnan; Thomas Lange; Maximilien Glorieux; Dan Alexandrescu; Maksim Jenihhin (AHS, 2019)

On the Estimation of Complex Circuits Functional Failure Rate by Machine Learning Techniques. - Thomas Lange; Aneesh Balakrishnan; Maximilien Glorieux; Dan Alexandrescu; Luca Sterpone (DSN (Supplements), 2019)

Functional Failure Rate Due to Single-Event Transients in Clock Distribution Networks. - Thomas Lange; Maximilien Glorieux; Dan Alexandrescu; Luca Sterpone (DTIS, 2019)

Machine Learning to Tackle the Challenges of Transient and Soft Errors in Complex Circuits. - Thomas Lange; Aneesh Balakrishnan; Maximilien Glorieux; Dan Alexandrescu; Luca Sterpone (IOLTS, 2019)

The Validation of Graph Model-Based, Gate Level Low-Dimensional Feature Data for Machine Learning Applications. - Aneesh Balakrishnan; Thomas Lange; Maximilien Glorieux; Dan Alexandrescu; Maksim Jenihhin (NORCAS, 2019)

Enabling Cross-Layer Reliability and Functional Safety Assessment Through ML-Based Compact Models. - Dan Alexandrescu; Aneesh Balakrishnan; Thomas Lange; Maximilien Glorieux (IOLTS, 2020)

Machine Learning Clustering Techniques for Selective Mitigation of Critical Design Features. - Thomas Lange; Aneesh Balakrishnan; Maximilien Glorieux; Dan Alexandrescu; Luca Sterpone (IOLTS, 2020)

Composing Graph Theory and Deep Neural Networks to Evaluate SEU Type Soft Error Effects. - Aneesh Balakrishnan; Thomas Lange; Maximilien Glorieux; Dan Alexandrescu; Maksim Jenihhin (MECO, 2020)

Gate-Level Graph Representation Learning: A Step Towards the Improved Stuck-at Faults Analysis. - Aneesh Balakrishnan; Dan Alexandrescu; Maksim Jenihhin; Thomas Lange; Maximilien Glorieux (ISQED, 2021)