1 citations · 1 across the 3 of their papers we have counts for
4 papers
PPAAS: PVT and Pareto Aware Analog Sizing via Goal-conditioned Reinforcement Learning
Seunggeun Kim, Ziyi Wang, Sungyoung Lee +4
Device sizing is a critical yet challenging step in analog and mixed-signal circuit design, requiring careful optimization to meet diverse performance specifications. This challeng…
Neural Variance-aware Dueling Bandits with Deep Representation and Shallow Exploration
Youngmin Oh, Jinje Park, Taejin Paik
We introduce the first variance-aware algorithms for contextual dueling bandits that leverage shallow exploration strategies with neural networks for nonlinear utility approximatio…
M3: Mamba-assisted Multi-Circuit Optimization via MBRL with Effective Scheduling
Youngmin Oh, Jinje Park, Seunggeun Kim +3
Recent advancements in reinforcement learning (RL) for analog circuit optimization have demonstrated significant potential for improving sample efficiency and generalization across…
INSIGHT: Universal Neural Simulator for Analog Circuits Harnessing Autoregressive Transformers
Souradip Poddar, Youngmin Oh, Yao Lai +3
Analog front-end design heavily relies on specialized human expertise and costly trial-and-error simulations, which motivated many prior works on analog design automation. However,…