| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| CIFAR-10 | Sampling Time (s)0.3 | 39 | 1mo ago | ||
| DW-4 8 dimensions standard Gaussian reference | Neural Calls0 | 24 | 23d ago | ||
| GMM-10 N=30 chains | CMCD-APT | R Value6,231 | 9 | 23d ago | |
| GMM-10 (N=10 chains) | R681 | 9 | 23d ago | ||
| GMM-10 N=6 chains | CMCD-APT | R1,743 | 9 | 23d ago | |
| ImageNet 32x32 | L3C | Sampling Time (s)0.0006 | 9 | 1mo ago | |
| ManyWell-32 N=30 chains | CMCD-APT | Lambda_hat_K Statistic3.148 | 8 | 23d ago | |
| ManyWell-32 (N=10 chains) | Diff-APT | R Statistic5,704 | 8 | 23d ago | |
| ManyWell-32 N=5 chains | Diff-PT | R251 | 8 | 23d ago | |
| swissroll | DPF | Transport Efficiency99.47 | 6 | 1mo ago | |
| pinwheel | DPF | Transport Efficiency99.5 | 6 | 1mo ago | |
| moons | DPF | Transport Efficiency99.63 | 6 | 1mo ago | |
| circles | DPF | Transport Efficiency99.23 | 6 | 1mo ago | |
| checkerboard | DPF | Transport Efficiency99.02 | 6 | 1mo ago | |
| 8gaussians | DPF | Transport Efficiency99.54 | 6 | 1mo ago | |
| 2spirals | DPF | Transport Efficiency98.99 | 6 | 1mo ago | |
| VMAS | CoHetteam | Mean Episodic Reward34.86 | 4 | 1mo ago | |
| MNIST | i-ResNet | Sampling Time (s)11.56 | 3 | 1mo ago | |
| Pybullet | Wall-Clock Time (ms)16.5 | 2 | 1mo ago | ||
| Discrete Data Masking Noising | - | - | 0 | 1mo ago | |
| Discrete Data Uniform Noising | - | - | 0 | 1mo ago | |
| Product distributions with p_j in [1/3, 2/3] | - | - | 0 | 1mo ago | |
| Product distributions on {0, 1}^d | - | - | 0 | 1mo ago | |
| Distributions on [k] | - | - | 0 | 1mo ago | |
| Theoretical Distributions | - | - | 0 | 1mo ago |
