Machine Learning Efficiency on Mixed Tabular Datasets (Adult, Default, Shoppers, Magic, Beijing, News) benchmark leaderboard · SOTA2 Research

Machine Learning Efficiency on Mixed Tabular Datasets (Adult, Default, Shoppers, Magic, Beijing, News)

92.7AUC (Adult)Real

Evaluation Results

Method	Links
Real2026.05		92.7	77	92.6	94.6	0.423	0.842	0
GReaT2026.05		91.3	75.5	90.2	88.8	0.653	—	13.3
TABSYN2026.05		91.1	76	91.3	94.2	0.663	0.82	10.7
PGE-TABSYN2026.05		91	74	91.3	93.9	0.642	2.24	37.61
TabDDPM2026.05		90.7	75.8	91.8	93.5	0.592	4.86	9.14
STaSy2026.05		90.6	75.2	91.4	93.4	0.656	0.871	10.9
TABKDE2026.05		90.6	74.5	91.7	93.4	0.675	0.869	11.76
COPULADIFF2026.05		90.1	76.3	91.2	93.9	0.667	0.921	12.18
SIMPLE-KDE2026.05		90.1	73	91.3	93.1	0.756	1.167	21.39
SMOTE2026.05		89.9	74.1	91.1	93.4	0.593	0.897	9.39
TABKDE2026.05		89.8	73.3	90.1	93.2	0.683	0.865	12.72
VAESIMPLEKDE2026.05		89.6	73.3	87.4	91.2	0.777	1.037	20.7
VAETABKDE2026.05		89	74.7	87.1	91.3	0.649	0.86	11.2
TABKDE2026.05		89	74.2	91.3	92.4	0.695	0.878	13.32
CTGAN2026.05		88.6	69.6	87.5	85.5	0.902	0.88	24.5
RANDCORETABKDE2026.05		88.3	73	91.1	92.9	0.713	0.881	14.42
CORETABKDE2026.05		88.1	71.2	91.9	92.8	0.744	0.877	15.86
TVAE2026.05		87.8	72.4	87.1	88.7	0.77	1.01	20.9
CoDi2026.05		87.1	52.5	86.5	93.2	0.818	1.21	30.5
GOGGLE2026.05		77.8	58.4	65.8	65.4	1.09	0.877	43.6