Image Classification on BloodMNIST (test)
96.71AccuracyDistributional Loss
Evaluation Results
| Method | Links | |
|---|---|---|
| Distributional LossSamples per Class=full dataset, Density Estimate=KDE2026.06 | 96.71 | |
| T-vMFSamples per Class=full dataset2026.06 | 96.05 | |
| CESamples per Class=full dataset2026.06 | 95.4 | |
| PolyLossSamples per Class=full dataset2026.06 | 95.29 | |
| Distributional LossSamples per Class=200, Density Estimate=KDE2026.06 | 92.32 | |
| PolyLossSamples per Class=2002026.06 | 92.14 | |
| T-vMFSamples per Class=2002026.06 | 92.01 | |
| CESamples per Class=2002026.06 | 90.06 | |
| Distributional LossSamples per Class=20, Density Estimate=KDE2026.06 | 83.14 | |
| T-vMFSamples per Class=202026.06 | 79.9 | |
| PolyLossSamples per Class=202026.06 | 78.65 | |
| FedKT-CSD (DP)Data Partitioning=Path.2026.07 | 75.19 | |
| FedKT-CSD (DP)Data Partitioning=α=0.12026.07 | 75.03 | |
| FedKT-CSD (DP)Data Partitioning=α=0.052026.07 | 74.84 | |
| CESamples per Class=202026.06 | 73.35 | |
| FedSD2CData Partitioning=α=0.12026.07 | 69.52 | |
| FedSD2CData Partitioning=Path.2026.07 | 65.47 | |
| FedSD2CData Partitioning=α=0.052026.07 | 61.83 | |
| Distributional LossSamples per Class=2, Density Estimate=KDE2026.06 | 61.82 | |
| DENSEData Partitioning=α=0.12026.07 | 58.46 | |
| T-vMFSamples per Class=22026.06 | 55.45 | |
| DENSEData Partitioning=Path.2026.07 | 54.83 | |
| CoBoostingData Partitioning=α=0.12026.07 | 54.82 | |
| FedCVAEData Partitioning=Path.2026.07 | 51.83 | |
| PolyLossSamples per Class=22026.06 | 51.63 | |
| CoBoostingData Partitioning=Path.2026.07 | 51.47 | |
| FedD3Data Partitioning=Path.2026.07 | 50.27 | |
| FedCVAEData Partitioning=α=0.12026.07 | 50.15 | |
| DENSEData Partitioning=α=0.052026.07 | 48.72 | |
| FedD3Data Partitioning=α=0.12026.07 | 48.36 | |
| CoBoostingData Partitioning=α=0.052026.07 | 45.63 | |
| FedCVAEData Partitioning=α=0.052026.07 | 45.28 | |
| CESamples per Class=22026.06 | 44.63 | |
| FedD3Data Partitioning=α=0.052026.07 | 43.85 |