Awais, M., Ghasemzadeh Mohammadi, H., &; Platzner, M. (2024). DeepApprox: Rapid Deep Learning based Design Space Exploration of Approximate Circuits via Check-pointing. To Apear in IEEE ISVLSI 2024. IEEE Computer Society Annual Symposium on VLSI, Knoxville, Tennessee, USA.

Awais, M., Ghasemzadeh Mohammadi, H., &; Platzner, M. (2021). 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 (pp. 27–32). Virtual: ACM.https://doi.org/10.1145/3453688.3461506 

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

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

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

Witschen, L. M., Wiersema, T., Ghasemzadeh Mohammadi, H., Awais, M., &; Platzner, M. (n.d.). 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. (2018). An MCTS-based Framework for Synthesis of Approximate Circuits. In 26th IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC) (pp. 219–224).https://doi.org/10.1109/VLSI-SoC.2018.8645026