Mutual Information Estimation on Low-Dimensional Benchmark S=2 to 50, D=10 (test)
31.03MI EstimateDBMI
Evaluation results
| Method | Links | ||
|---|---|---|---|
| DBMINumber of Categories (S)=50, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 31.03 | 32.73 | |
| DBMINumber of Categories (S)=25, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 25.33 | 25.86 | |
| DBMINumber of Categories (S)=10, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 16.9 | 16.8 | |
| DBMINumber of Categories (S)=5, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 10.21 | 10.35 | |
| f-DIME-GNumber of Categories (S)=25, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 9.97 | 25.86 | |
| MINENumber of Categories (S)=25, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 9.8 | 25.86 | |
| MINENumber of Categories (S)=50, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 9.71 | 32.73 | |
| f-DIME-GNumber of Categories (S)=10, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 9.23 | 16.8 | |
| f-DIME-GNumber of Categories (S)=50, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 8.65 | 32.73 | |
| f-DIME-HNumber of Categories (S)=5, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 7.44 | 10.35 | |
| f-DIME-HNumber of Categories (S)=50, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 7.11 | 32.73 | |
| f-DIME-HNumber of Categories (S)=10, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 7.01 | 16.8 | |
| f-DIME-GNumber of Categories (S)=5, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 6.97 | 10.35 | |
| MINENumber of Categories (S)=5, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 6.82 | 10.35 | |
| InfoNCENumber of Categories (S)=10, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 6.21 | 16.8 | |
| InfoNCENumber of Categories (S)=25, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 6.21 | 25.86 | |
| InfoNCENumber of Categories (S)=50, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 6.18 | 32.73 | |
| InfoNCENumber of Categories (S)=5, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 6.13 | 10.35 | |
| f-DIME-KLNumber of Categories (S)=10, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 5.04 | 16.8 | |
| f-DIME-KLNumber of Categories (S)=5, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 4.65 | 10.35 | |
| f-DIME-KLNumber of Categories (S)=25, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 4.42 | 25.86 | |
| DBMINumber of Categories (S)=2, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 3.91 | 3.64 | |
| f-DIME-GNumber of Categories (S)=2, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 3.84 | 3.64 | |
| f-DIME-KLNumber of Categories (S)=50, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 3.57 | 32.73 | |
| f-DIME-HNumber of Categories (S)=2, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 3.37 | 3.64 | |
| MINENumber of Categories (S)=2, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 3.28 | 3.64 | |
| MINENumber of Categories (S)=10, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 3.28 | 16.8 | |
| f-DIME-KLNumber of Categories (S)=2, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 3.08 | 3.64 | |
| InfoNCENumber of Categories (S)=2, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | 2.909 | 3.64 | |
| f-DIME-HNumber of Categories (S)=25, Dimension (D)=10, Number of training samples=10^4, Number of test samples=10^42026.02 | -9.65 | 25.86 |