Towards Explainable Bit Error Tolerance of Resistive RAM-Based Binarized Neural Networks. - Sebastian Buschjäger; Jian-Jia Chen; Kuan-Hsun Chen; Mario Günzel; Christian Hakert; Katharina Morik; Rodion Novkin; Lukas Pfahler; Mikail Yayla (CoRR, 2020)

Margin-Maximization in Binarized Neural Networks for Optimizing Bit Error Tolerance. - Sebastian Buschjäger; Jian-Jia Chen; Kuan-Hsun Chen; Mario Günzel; Christian Hakert; Katharina Morik; Rodion Novkin; Lukas Pfahler; Mikail Yayla (DATE, 2021)

Bit Error Tolerance Metrics for Binarized Neural Networks. - Sebastian Buschjäger; Jian-Jia Chen; Kuan-Hsun Chen; Mario Günzel; Katharina Morik; Rodion Novkin; Lukas Pfahler; Mikail Yayla (CoRR, 2021)

Comprehensive Reliability Analysis of 22nm FDSOI SRAM from Device Physics to Deep Learning. - Om Prakash 007; Rodion Novkin; Virinchi Roy Surabhi; Prashanth Krishnamurthy; Ramesh Karri; Farshad Khorrami; Hussam Amrouch (ISCAS, 2023)

ML-TCAD: Perspectives and Challenges on Accelerating Transistor Modeling using ML. - Rodion Novkin; Simon Thomann; Hussam Amrouch (MLCAD, 2023)

Frontiers in Edge AI with RISC-V: Hyperdimensional Computing vs. Quantized Neural Networks. - Paul R. Genssler; Sandy A. Wasif; Miran Wael; Rodion Novkin; Hussam Amrouch (DATE, 2024)

Approximation- and Quantization-Aware Training for Graph Neural Networks. - Rodion Novkin; Florian Klemme; Hussam Amrouch (IEEE Trans. Computers, 2024)

Kolmogorov-Arnold Network for Transistor Compact Modeling. - Rodion Novkin; Hussam Amrouch (CoRR, 2025)