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We have proposed NAS-Bench-Graph (paper, code, tutorial), the first NAS-benchmark for graphs published in NeurIPS'22. By using AutoGL together with NAS-Bench-Graph, the performance estimation process of GraphNAS algorithms can be greatly speeded up.
We have supported the graph robustness algorithms in AutoGL, including graph structure engineering, robust GNNs and robust GraphNAS. See robustness tutorial for more details.