1. [1] Laung-Terng Wang, Yao-Wen Chang, and Kwang-Ting Tim Cheng. Electronic Design Automation: Synthesis, Verification, and Test. Morgan Kaufmann, 2009.
2. Machine Learning Applications in Electronic Design Automation
3. [3] Chi-Hsien Pao, An-Yu Su, and Yu-Min Lee. XGBIR: An XGBoost-based IR Drop Predictor for Power Delivery Network. IEEE/ACM Proceedings Design, Automation and Test in Europe (DATE), pp. 1307–1310, 2020.
4. [4] Tianqi Chen and Carlos Guestrin. XGBoost: A Scalable Tree Boosting System. ACM International Conference on Knowledge Discovery and Data Mining (KDD), pp. 785–794, 2016.
5. PowerNet: Transferable Dynamic IR Drop Estimation via Maximum Convolutional Neural Network