Image Classification on ImageNet-1K (Acc, Brier, NLL, ECE, aECE) benchmark leaderboard · SOTA2 Research

Image Classification on ImageNet-1K (Acc, Brier, NLL, ECE, aECE)

82.19AccuracyDEEP ENSEMBLES

Evaluation Results

Method	Links
DEEP ENSEMBLES2025.10		82.19	0.25	0.65	0.01	0.01
HYDRA ENS (TAYLOR)2025.10		81.2	0.26	0.75	0.01	0.01
HYDRA ENS (CIRC)2025.10		80.88	0.27	0.74	0.01	0.01
LORA ENSEMBLES2025.10		80.68	0.27	0.71	0.01	0.01
TAYLOR2025.10		80.68	0.28	0.79	0.02	0.02
SINGLE2025.10		80.67	0.27	0.71	0.01	0.01
MIMO2025.10		80.59	0.27	0.72	0.01	0.01
BATCH ENSEMBLES2025.10		80.53	0.27	0.72	0.01	0.01
MC DROPOUT2025.10		80.3	0.28	0.73	0.02	0.02
CIRCAVG2025.10		80.22	0.28	0.77	0.02	0.02
PACKED ENSEMBLES2025.10		79.23	0.29	0.78	0.01	0.01
OBA2025.10		78.52	0.3	0.85	0.03	0.03