SlowGuess/NeurIPS_2023_OCR huggingface dataset:
Table 4: Comparative results of tree topology diversity statistics for DS1, DS4, and DS7 datasets using MrBayes, VBPI-GNN, and GeoPhy. Statistics presented include (a) the Simpson's diversity index, (b) the frequency of the most frequent topology, and (c) the number of topologies accounting for the top  $95\%$  cumulative frequency.
Dataset	Statistics	MrBayes	VBPI-GNN	GeoPhy
DS1	(a)	0.874	0.891	0.362
(b)	0.268	0.313	0.793
(c)	42	44	11
DS4	(a)	0.895	0.895	0.678
(b)	0.277	0.285	0.554
(c)	208	90	58
DS7	(a)	0.988	0.991	0.996
(b)	0.022	0.028	0.022
(c)	753	315	553
Figure 9: Left: Comparison of convergence curves for different per-step MC samples ( $K = 2,3,5,10$ ) in dataset DS1. Right: Comparison of convergence in dataset DS1 for different link functions, NJ and UPGMA, that map coordinates into tree topologies  $\tau(z)$ .
Figure 10: Left: Single-core runtime comparison of MrBayes, VBPI-GNN, and GeoPhy (ours). MrBayes SS* represents one of ten runs used for MrBayes SS. VBPI-GNN is trained for 400k iterations with  $K = 10$  MC samples. For VBPI-GNN* and GeoPhy (ours), we represent runtimes for training with 1M MC samples. For GeoPhy, we employed a 2d-diagonal normal distribution for  $Q(z)$  and LOO+LAX for control variates (CVs). Right: CPU-time per 1k MC samples for two types of distribution  $Q(z)$  across eight datasets. We compared LOO or LOO+LAX for CVs.