Awais M, Ghasemzadeh Mohammadi H, Platzner M. DeepApprox: Rapid Deep Learning based Design Space Exploration of Approximate Circuits via Check-pointing. In: To Apear in IEEE ISVLSI 2024. ; 2024.

Awais M, Ghasemzadeh Mohammadi H, Platzner M. LDAX: A Learning-based Fast Design Space Exploration Framework for Approximate Circuit Synthesis. In: Proceedings of the ACM Great Lakes Symposium on VLSI (GLSVLSI) 2021. ACM; 2021:27-32. doi:https://doi.org/10.1145/3453688.3461506

Awais M, Platzner M. MCTS-Based Synthesis Towards Efficient Approximate Accelerators. In: Proceedings of IEEE Computer Society Annual Symposium on VLSI. IEEE; 2021:384-389.

Awais M, Ghasemzadeh Mohammadi H, Platzner M. A Hybrid Synthesis Methodology for Approximate Circuits. In: Proceedings of the 30th ACM Great Lakes Symposium on VLSI (GLSVLSI) 2020. ACM; 2020:421-426. doi:10.1145/3386263.3406952

Witschen LM, Wiersema T, Ghasemzadeh Mohammadi H, Awais M, Platzner M. CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation. Microelectronics Reliability. 2019;99:277-290. doi:10.1016/j.microrel.2019.04.003

Witschen LM, Wiersema T, Ghasemzadeh Mohammadi H, Awais M, Platzner M. CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation. Third Workshop on Approximate Computing (AxC 2018).

Awais M, Ghasemzadeh Mohammadi H, Platzner M. An MCTS-based Framework for Synthesis of Approximate Circuits. In: 26th IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC). ; 2018:219-224. doi:10.1109/VLSI-SoC.2018.8645026