Papers with Code 아카이브

Bayesian Optimization

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
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데이터셋

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OCB

OCB contains two graph datasets, Ckt-Bench-101 and Ckt-Bench-301, for representation learning over analog circuits. Ckt-Bench-101 and Ckt-Bench-301 contain graphs (DAGs) that represent analog circuits and provide their corresponding graph-level properties: DC gain (Gain), bandwidth (BW), phase margin (PM),Figure of Merit (FoM), which characterize the circuit performance. * Motivation: Facilitate research in representation learning and automation of analog circuits. * Tasks: graph-level prediction/regression; analog circuit search (ACS). * Node features: discrete feature that characterize device type (e.g. capacitor); and continues feature of the device (e.g. capacitance). * First open source benchmark for graph learning in analog circuits.

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.