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Graph Alignment on Dense Erdős-Rényi graphs (average degree 80)

100AccuracyPROJ(DCX)
-2.9623.7750.577.23Oct 3, 2025
Updated 5mo ago

Evaluation results

MethodLinks
PROJ(DCX)pNOISE=02025.1010019,964
PROJ(DCX)pNOISE=0.052025.1010018,987
PROJ(DCX)pNOISE=0.12025.1010017,966
FAQ(DCX)pNOISE=02025.1010019,964
FAQ(DCX)pNOISE=0.052025.1010018,987
FAQ(DCX)pNOISE=0.12025.1010017,968
FAQ(DCX)pNOISE=0.152025.1010016,990
FAQ(DCX)pNOISE=0.22025.1010015,972
FGNN PROJpNOISE=02025.1010019,964
FGNN PROJpNOISE=0.052025.1010018,979
FGNN FAQpNOISE=02025.1010019,964
FGNN FAQpNOISE=0.052025.1010018,987
FGNN FAQpNOISE=0.12025.1010017,968
FGNN FAQpNOISE=0.152025.1010016,990
CHFGNN PROJpNOISE=02025.1010019,964
CHFGNN PROJpNOISE=0.052025.1010018,987
CHFGNN FAQpNOISE=02025.1010019,964
CHFGNN FAQpNOISE=0.052025.1010018,987
CHFGNN FAQpNOISE=0.12025.1010017,968
CHFGNN FAQpNOISE=0.152025.1010016,990
CHFGNN FAQpNOISE=0.22025.109915,972
FGNN FAQpNOISE=0.22025.109515,390
CHFGNN PROJpNOISE=0.12025.109416,241
CHFGNN PROJpNOISE=0.152025.108313,028
FGNN PROJpNOISE=0.12025.107311,254
CHFGNN PROJpNOISE=0.22025.106810,291
CHFGNN FAQpNOISE=0.252025.106211,577
PROJ(DCX)pNOISE=0.152025.10618,700
CHFGNN PROJpNOISE=0.252025.10376,574
FGNN PROJpNOISE=0.152025.10284,674
FAQ(DCX)pNOISE=0.252025.10217,922
PROJ(DCX)pNOISE=0.22025.10143,888
FGNN FAQpNOISE=0.252025.10147,031
FGNN PROJpNOISE=0.22025.10103,651
PROJ(DCX)pNOISE=0.252025.1043,646
FGNN PROJpNOISE=0.252025.1043,521
PROJ(DCX)pNOISE=0.32025.1023,633
FGNN PROJpNOISE=0.32025.1023,517
CHFGNN PROJpNOISE=0.32025.1023,690
PROJ(DCX)pNOISE=0.352025.1013,624
FAQ(DCX)pNOISE=0.32025.1016,272
FAQ(DCX)pNOISE=0.352025.1016,276
FGNN PROJpNOISE=0.352025.1013,505
FGNN FAQpNOISE=0.32025.1016,259
FGNN FAQpNOISE=0.352025.1016,254
CHFGNN PROJpNOISE=0.352025.1013,591
CHFGNN FAQpNOISE=0.32025.1016,263
CHFGNN FAQpNOISE=0.352025.1016,255