Renan Netto, Sheiny Fabre, Tiago Augusto Fontana, Vinicius S. Livramento, Laércio Lima Pilla, José Luís Güntzel. How Deep Learning Can Drive Physical Synthesis Towards More Predictable Legalization. In Ismail Bustany, William Swartz, editors, Proceedings of the 2019 International Symposium on Physical Design, ISPD 2019, San Francisco, CA, USA, April 14-17, 2019. pages 3-10, ACM, 2019. [doi]
@inproceedings{NettoFFLPG19,
title = {How Deep Learning Can Drive Physical Synthesis Towards More Predictable Legalization},
author = {Renan Netto and Sheiny Fabre and Tiago Augusto Fontana and Vinicius S. Livramento and Laércio Lima Pilla and José Luís Güntzel},
year = {2019},
doi = {10.1145/3299902.3309754},
url = {https://doi.org/10.1145/3299902.3309754},
researchr = {https://researchr.org/publication/NettoFFLPG19},
cites = {0},
citedby = {0},
pages = {3-10},
booktitle = {Proceedings of the 2019 International Symposium on Physical Design, ISPD 2019, San Francisco, CA, USA, April 14-17, 2019},
editor = {Ismail Bustany and William Swartz},
publisher = {ACM},
isbn = {978-1-4503-6253-5},
}