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 Tasks: graph-level prediction/regression; analog circuit search (ACS). First open source benchmark for graph learning in analog circuits.
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…EHR data are typically stored in a relational database, which can also be converted to a directed acyclic graph, allowing two approaches for EHR QA: Table-based QA and Knowledge Graph-based QA. MIMIC-SPARQL dataset provides graph-based EHR QA data where natural language queries are converted to SPARQL instead of SQL
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…Although existing space function classifiers use space adjacency or connectivity graphs as input, the application of Graph Deep Learning (GDL) to space layout element classification has not been extensively To bridge this gap, we introduce a dataset named SAGC-A68, which comprises access graphs automatically generated from 68 digital 3D models of space layouts of apartment buildings designed or built between Each access graph contains nodes representing spaces and space elements and edges representing the connection between them.