Mar 18, 2023 · We present GenCAT Workbench, an end-to-end framework with which users can generate synthetic attributed graphs with node labels and evaluate ...
Mar 18, 2023 · We demonstrate the GenCAT Workbench and how it clarifies the strong and weak points of GNN models. Our code base is available on Github (https ...
We present GenCAT Workbench, an end-to-end framework with which users can generate synthetic attributed graphs with node labels and evaluate their graph ...
Abstract: We present GenCAT Workbench, an end-to-end framework with which users can generate synthetic attributed graphs with node labels and evaluate their ...
Abstract: We present GenCAT Workbench, an end-to-end framework with which users can generate synthetic attributed graphs with node labels and evaluate their ...
Bibliographic details on Benchmarking GNNs with GenCAT Workbench.
To understand the pros/cons of GNNs, we empirically study the performance of. GNNs through extensive experiments on various graphs by synthetically changing one ...
Missing: Workbench. | Show results with:Workbench.
Nov 14, 2024 · We show that our model is able to consistently replicate the learnability of graphs on graph convolutional, attention, and isomorphism networks ...
Oct 20, 2024 · 2022. Beyond Real-world Benchmark Datasets: An Empirical Study of Node Classification with GNNs. ... 2022. Benchmarking GNNs with GenCAT Workbench ...
This work introduces a comprehensive benchmarking framework for graph ... Benchmarking GNNs with GenCAT Workbench · Seiji MaekawaYuya SasakiG. Fletcher ...