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Policy Gradient Reinforcement Learning-based Optimal Decoupling Capacitor Design Method for 2.5-D/3-D ICs using Transformer Network

Research article (2020 IEEE Electrical Design of Advanced Packaging and Systems (EDAPS), 2020) · cited 11× · AI/ML
academia openalex:W3120186441
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Policy Gradient Reinforcement Learning-based Optimal Decoupling Capacitor Design Method for 2.5-D/3-D ICs using Transformer Network

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Policy Gradient Reinforcement Learning-based Optimal Decoupling Capacitor Design Method for 2.5-D/3-D ICs using Transformer Network is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Policy Gradient Reinforcement Learning-based Optimal Decoupling Capacitor Design Method for 2.5-D/3-D ICs using Transformer Network. Retrieved May 24, 2026, from https://4ort.xyz/entity/policy-gradient-reinforcement-learning-based-optimal-decoupling-capacitor-design-method-for-2-5-d-3-d-ics-using-transfor
MLA “Policy Gradient Reinforcement Learning-based Optimal Decoupling Capacitor Design Method for 2.5-D/3-D ICs using Transformer Network.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/policy-gradient-reinforcement-learning-based-optimal-decoupling-capacitor-design-method-for-2-5-d-3-d-ics-using-transfor.
BibTeX @misc{4ortxyz_policy-gradient-reinforcement-learning-based-optimal-decoupling-capacitor-design-method-for-2-5-d-3-d-ics-using-transfor_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Policy Gradient Reinforcement Learning-based Optimal Decoupling Capacitor Design Method for 2.5-D/3-D ICs using Transformer Network}}, year = {2026}, url = {https://4ort.xyz/entity/policy-gradient-reinforcement-learning-based-optimal-decoupling-capacitor-design-method-for-2-5-d-3-d-ics-using-transfor}, note = {Accessed: 2026-05-24}}
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