Modeling gate-level abstraction hierarchy using graph convolutional neural networks to predict functional de-rating factorsBalakrishnan, Aneesh; Lange, Thomas; Glorieux, Maximilien; Alexandrescu, Dan; Jenihhin, Maksim2019 NASA/ESA conference on adaptive hardware and systems AHS 2019 : proceedings2019 / p. 72-78 : ill https://doi.org/10.1109/AHS.2019.00007

On the estimation of complex circuits functional failure rate by machine learning techniquesLange, Thomas; Balakrishnan, Aneesh; Glorieux, Maximilien; Alexandrescu, Dan; Sterpone, Luca49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks - DSN 2019 : Supplemental Volume : proceedings2019 / p. 35-41 : ill https://doi.org/10.1109/DSN-S.2019.00021

The validation of graph model-based, gate level low-dimensional feature data for machine learning applicationsBalakrishnan, Aneesh; Lange, Thomas; Glorieux, Maximilien; Alexandrescu, Dan; Jenihhin, Maksim2019 IEEE Nordic Circuits and Systems Conference (NORCAS) : NORCHIP and International Symposium of System-on-Chip (SoC), 29-30 October 2019, Helsinki, Finland : proceedings in IEEE Xplore2019 / 7 p https://doi.org/10.1109/NORCHIP.2019.8906974