2 citations · 2 across the 4 of their papers we have counts for
3 papers · 1 filter
FALCON: An ML Framework for Fully Automated Layout-Constrained Analog Circuit Design
Asal Mehradfar, Xuzhe Zhao, Yilun Huang +5
Designing analog circuits from performance specifications is a complex, multi-stage process encompassing topology selection, parameter inference, and layout feasibility. We introdu…
Supervised Learning for Analog and RF Circuit Design: Benchmarks and Comparative Insights
Asal Mehradfar, Xuzhe Zhao, Yue Niu +4
Automating analog and radio-frequency (RF) circuit design using machine learning (ML) significantly reduces the time and effort required for parameter optimization. This study expl…
Learning to Design Analog Circuits to Meet Threshold Specifications
Dmitrii Krylov, Pooya Khajeh, Junhan Ouyang +5
Automated design of analog and radio-frequency circuits using supervised or reinforcement learning from simulation data has recently been studied as an alternative to manual expert…