no code implementations • 20 Mar 2024 • Zhenyuan Yuan, Siyuan Xu, Minghui Zhu
This paper considers the problem of learning a control policy for robot motion planning with zero-shot generalization, i. e., no data collection and policy adaptation is needed when the learned policy is deployed in new environments.
no code implementations • 28 Feb 2024 • Ke Xue, Xi Lin, Yunqi Shi, Shixiong Kai, Siyuan Xu, Chao Qian
Placement is crucial in the physical design, as it greatly affects power, performance, and area metrics.
1 code implementation • 28 Dec 2023 • RuiZhe Zhong, Xingbo Du, Shixiong Kai, Zhentao Tang, Siyuan Xu, Hui-Ling Zhen, Jianye Hao, Qiang Xu, Mingxuan Yuan, Junchi Yan
Since circuit can be represented with HDL in a textual format, it is reasonable to question whether LLMs can be leveraged in the EDA field to achieve fully automated chip design and generate circuits with improved power, performance, and area (PPA).
no code implementations • 3 Feb 2023 • Siyuan Xu, Minghui Zhu
Bilevel optimization has been developed for many machine learning tasks with large-scale and high-dimensional data.