affected
发表于 2025-3-21 18:03:41
书目名称Machine Learning Applications in Electronic Design Automation影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0620382<br><br> <br><br>书目名称Machine Learning Applications in Electronic Design Automation影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0620382<br><br> <br><br>书目名称Machine Learning Applications in Electronic Design Automation网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0620382<br><br> <br><br>书目名称Machine Learning Applications in Electronic Design Automation网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0620382<br><br> <br><br>书目名称Machine Learning Applications in Electronic Design Automation被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0620382<br><br> <br><br>书目名称Machine Learning Applications in Electronic Design Automation被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0620382<br><br> <br><br>书目名称Machine Learning Applications in Electronic Design Automation年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0620382<br><br> <br><br>书目名称Machine Learning Applications in Electronic Design Automation年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0620382<br><br> <br><br>书目名称Machine Learning Applications in Electronic Design Automation读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0620382<br><br> <br><br>书目名称Machine Learning Applications in Electronic Design Automation读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0620382<br><br> <br><br>
deriver
发表于 2025-3-21 23:55:15
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不感兴趣
发表于 2025-3-22 03:56:11
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inconceivable
发表于 2025-3-22 06:16:29
https://doi.org/10.1007/978-3-031-13074-8Deep learning for EDA; convolutional neural networks; graph neural networks; generative adversarial net
FID
发表于 2025-3-22 12:08:36
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Aerate
发表于 2025-3-22 16:27:38
deep learning models such as convolutional neural networks .This book serves as a single-source reference to key machine learning (ML) applications and methods in digital and analog design and verification. Experts from academia and industry cover a wide range of the latest research on ML applicat
Trabeculoplasty
发表于 2025-3-22 17:09:00
Book 2022 convolutional neural networks (CNNs), graph neural networks (GNNs), generative adversarial networks (GANs) and optimization methods such as reinforcement learning (RL) and Bayesian optimization (BO). All of these topics are valuable to chip designers and EDA developers and researchers working in digital and analog designs and verification. .
DEVIL
发表于 2025-3-23 00:37:44
Deep Learning Framework for Placementmeworks to accelerate kernel placement solvers as well as integrating machine learning models to speed up cross-layer optimization. We hope this line of studies can broaden the applications of machine learning techniques in IC design automation and stimulate more researches in related fields.
描绘
发表于 2025-3-23 02:37:48
Machine Learning in the Service of Hardware Functional Verificationconnect the various verification tools and data sources and create a unified data repository in a data warehouse that is optimized for data retrieval. This connection allows the use of advanced data science techniques that improve the quality of the entire verification process.
bronchodilator
发表于 2025-3-23 09:08:32
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