Sliced Wasserstein Distance Estimation on Gaussian toy samples d=30
0.0638Averaged SW1i.i.d.
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| i.i.d.T=10000, MCMC Algorithm=regular NUTS, d=302025.09 | 0.0638 | 7 | |
| RepelledT=10000, MCMC Algorithm=regular NUTS, d=302025.09 | 0.0638 | 8 | |
| UnifOrthoT=10000, MCMC Algorithm=regular NUTS, d=302025.09 | 0.0638 | 3 | |
| i.i.d.T=10000, MCMC Algorithm=broken NUTS, d=302025.09 | 0.0645 | 8 | |
| RepelledT=10000, MCMC Algorithm=broken NUTS, d=302025.09 | 0.0645 | 8 | |
| UnifOrthoT=10000, MCMC Algorithm=broken NUTS, d=302025.09 | 0.0646 | 3 | |
| i.i.d.T=10000, MCMC Algorithm=regular HMC, d=302025.09 | 0.134 | 0.002 | |
| RepelledT=10000, MCMC Algorithm=regular HMC, d=302025.09 | 0.134 | 0.002 | |
| UnifOrthoT=10000, MCMC Algorithm=regular HMC, d=302025.09 | 0.1341 | 6 | |
| i.i.d.T=10000, MCMC Algorithm=broken HMC, d=302025.09 | 0.169 | 0.002 | |
| RepelledT=10000, MCMC Algorithm=broken HMC, d=302025.09 | 0.169 | 0.002 | |
| UnifOrthoT=10000, MCMC Algorithm=broken HMC, d=302025.09 | 0.1693 | 6 | |
| i.i.d.T=1000, MCMC Algorithm=regular NUTS, d=302025.09 | 0.215 | 0.003 | |
| RepelledT=1000, MCMC Algorithm=regular NUTS, d=302025.09 | 0.215 | 0.003 | |
| UnifOrthoT=1000, MCMC Algorithm=regular NUTS, d=302025.09 | 0.215 | 0.001 | |
| i.i.d.T=1000, MCMC Algorithm=broken NUTS, d=302025.09 | 0.236 | 0.003 | |
| RepelledT=1000, MCMC Algorithm=broken NUTS, d=302025.09 | 0.236 | 0.003 | |
| UnifOrthoT=1000, MCMC Algorithm=broken NUTS, d=302025.09 | 0.236 | 0.001 | |
| i.i.d.T=1000, MCMC Algorithm=regular HMC, d=302025.09 | 0.288 | 0.003 | |
| RepelledT=1000, MCMC Algorithm=regular HMC, d=302025.09 | 0.288 | 0.004 | |
| UnifOrthoT=1000, MCMC Algorithm=regular HMC, d=302025.09 | 0.288 | 0.001 | |
| i.i.d.T=1000, MCMC Algorithm=broken HMC, d=302025.09 | 0.363 | 0.005 | |
| RepelledT=1000, MCMC Algorithm=broken HMC, d=302025.09 | 0.363 | 0.004 | |
| UnifOrthoT=1000, MCMC Algorithm=broken HMC, d=302025.09 | 0.363 | 0.001 | |
| i.i.d.T=100, MCMC Algorithm=regular NUTS, d=302025.09 | 0.529 | 0.007 | |
| RepelledT=100, MCMC Algorithm=regular NUTS, d=302025.09 | 0.529 | 0.008 | |
| UnifOrthoT=100, MCMC Algorithm=regular NUTS, d=302025.09 | 0.529 | 0.003 | |
| RepelledT=100, MCMC Algorithm=broken HMC, d=302025.09 | 0.725 | 0.009 | |
| UnifOrthoT=100, MCMC Algorithm=broken HMC, d=302025.09 | 0.725 | 0.004 | |
| i.i.d.T=100, MCMC Algorithm=broken HMC, d=302025.09 | 0.726 | 0.009 | |
| RepelledT=100, MCMC Algorithm=regular HMC, d=302025.09 | 0.848 | 0.011 | |
| UnifOrthoT=100, MCMC Algorithm=regular HMC, d=302025.09 | 0.848 | 0.004 | |
| i.i.d.T=100, MCMC Algorithm=regular HMC, d=302025.09 | 0.849 | 0.013 | |
| RepelledT=10, MCMC Algorithm=regular HMC, d=302025.09 | 1.918 | 0.01 | |
| UnifOrthoT=10, MCMC Algorithm=regular HMC, d=302025.09 | 1.918 | 0.001 | |
| i.i.d.T=10, MCMC Algorithm=regular HMC, d=302025.09 | 1.919 | 0.01 | |
| i.i.d.T=10, MCMC Algorithm=broken HMC, d=302025.09 | 2.135 | 0.017 | |
| RepelledT=10, MCMC Algorithm=broken HMC, d=302025.09 | 2.135 | 0.017 | |
| UnifOrthoT=10, MCMC Algorithm=broken HMC, d=302025.09 | 2.135 | 0.002 | |
| i.i.d.T=10, MCMC Algorithm=broken NUTS, d=302025.09 | 4.057 | 0.067 | |
| RepelledT=10, MCMC Algorithm=broken NUTS, d=302025.09 | 4.063 | 0.078 | |
| UnifOrthoT=10, MCMC Algorithm=broken NUTS, d=302025.09 | 4.063 | 0.018 | |
| i.i.d.T=100, MCMC Algorithm=broken NUTS, d=302025.09 | 4.242 | 0.077 | |
| UnifOrthoT=100, MCMC Algorithm=broken NUTS, d=302025.09 | 4.247 | 0.02 | |
| RepelledT=100, MCMC Algorithm=broken NUTS, d=302025.09 | 4.251 | 0.079 | |
| i.i.d.T=10, MCMC Algorithm=regular NUTS, d=302025.09 | 4.717 | 0.089 | |
| RepelledT=10, MCMC Algorithm=regular NUTS, d=302025.09 | 4.718 | 0.086 | |
| UnifOrthoT=10, MCMC Algorithm=regular NUTS, d=302025.09 | 4.719 | 0.022 |