Table 5.
Results for the distribution learning Guacamol benchmarks
| Case | Min increase | Max increase | Max replacements | Validity | Uniqueness | Novelty | KL divergence | Frechet ChemNet Distance |
|---|---|---|---|---|---|---|---|---|
| CReM | − 2 | 2 | 100 | 1 ± 0 | 0.935 ± 0.021 | 1 ± 0 | 0.443 ± 0.023 | 0.021 ± 0.007 |
| CReM | − 2 | 2 | 10 | 1 ± 0 | 0.942 ± 0.008 | 1 ± 0 | 0.530 ± 0.061 | 0.024 ± 0.034 |
| CReM | − 2 | 2 | 5 | 1 ± 0 | 0.941 ± 0.003 | 1 ± 0 | 0.572 ± 0.038 | 0.044 ± 0.053 |
| CReM | − 2 | 2 | 2 | 1 ± 0 | 0.950 ± 0.002 | 1 ± 0 | 0.551 ± 0.054 | 0.019 ± 0.018 |
| CReM | − 6 | 6 | 100 | 1 ± 0 | 0.942 ± 0.023 | 0.999 ± 0 | 0.541 ± 0.056 | 0.018 ± 0.012 |
| CReM | − 6 | 6 | 10 | 1 ± 0 | 0.924 ± 0.010 | 1 ± 0 | 0.603 ± 0.019 | 0.041 ± 0.045 |
| CReM | − 6 | 6 | 5 | 1 ± 0 | 0.921 ± 0.022 | 1 ± 0 | 0.584 ± 0.034 | 0.038 ± 0.040 |
| CReM | − 6 | 6 | 2 | 1 ± 0 | 0.935 ± 0.009 | 1 ± 0 | 0.605 ± 0.015 | 0.053 ± 0.050 |
| CReM | − 10 | 10 | 100 | 1 ± 0 | 0.918 ± 0.019 | 1 ± 0 | 0.531 ± 0.058 | 0.071 ± 0.027 |
| CReM | − 10 | 10 | 10 | 1 ± 0 | 0.907 ± 0.022 | 0.999 ± 0.001 | 0.622 ± 0.011 | 0.030 ± 0.016 |
| CReM | − 10 | 10 | 5 | 1 ± 0 | 0.875 ± 0.025 | 1 ± 0 | 0.599 ± 0.035 | 0.085 ± 0.056 |
| CReM | − 10 | 10 | 2 | 1 ± 0 | 0.850 ± 0.094 | 1 ± 0 | 0.590 ± 0.064 | 0.006 ± 0.005 |
| CReM | − 10 | 2 | 100 | 1 ± 0 | 0.945 ± 0.021 | 0.999 ± 0 | 0.550 ± 0.037 | 0.016 ± 0.012 |
| CReM | − 10 | 2 | 10 | 1 ± 0 | 0.950 ± 0.008 | 1 ± 0 | 0.545 ± 0.007 | 0.045 ± 0.010 |
| CReM | − 10 | 2 | 5 | 1 ± 0 | 0.956 ± 0.001 | 1 ± 0 | 0.533 ± 0.073 | 0.048 ± 0.036 |
| CReM | − 10 | 2 | 2 | 1 ± 0 | 0.962 ± 0.006 | 1 ± 0 | 0.577 ± 0.027 | 0.042 ± 0.037 |
| SMILES LSTM* | 0.959 | 1 | 0.912 | 0.991 | 0.913 | |||
| Graph MCTS* | 1 | 1 | 0.994 | 0.522 | 0.015 | |||
| AAE* | 0.822 | 1 | 0.988 | 0.886 | 0.529 | |||
| ORGAN* | 0.379 | 0.841 | 0.687 | 0.267 | 0 | |||
| VAE* | 0.870 | 0.999 | 0.974 | 0.982 | 0.963 |
* Results were taken from the ref [38]