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Table 2 Results of re-ranking combined proposals of GLN and RetroSim on USPTO-50K test data

From: Improving the performance of models for one-step retrosynthesis through re-ranking

Models

Top-N accuracy (%)

Mean Reciprocal Rank

1

3

5

10

20

50

RetroSim

35.7 (\(\pm 0\))

53.3 (\(\pm 0\))

62.0 (\(\pm 0\))

73.4 (\(\pm 0\))

82.3 (\(\pm 0\))

88.5 (\(\pm 0\))

0.477 (\(\pm 0.000\))

RetroSim + Graph-EBM

51.8 (\(\pm 0.43\))

74.5 (\(\pm 0.37\))

81.1 (\(\pm 0.17\))

86.4 (\(\pm 0.13\))

88.5 (\(\pm 0.02\))

88.9 (\(\pm 0.00\))

0.644 (\(\pm 0.004\))

GLN

51.7 (\(\pm 0.33\))

67.8 (\(\pm 0.43\))

75.1 (\(\pm 0.32\))

83.2 (\(\pm 0.12\))

88.9 (\(\pm 0.11\))

92.4 (\(\pm 0.06\))

0.620 (\(\pm 0.003\))

GLN + Graph-EBM

52.3 (\(\pm 0.01\))

74.9 (\(\pm 0.27\))

82.0 (\(\pm 0.18\))

88.0 (\(\pm 0.02\))

91.4 (\(\pm 0.11\))

93.0 (\(\pm 0.08\))

0.652 (\(\pm 0.001\))

GLN + RetroSim + Graph-EBM

52.5 (\(\pm 0.10\))

75.7 (\(\pm 0.15\))

83.1 (\(\pm 0.34\))

89.7 (\(\pm 0.18\))

93.1 (\(\pm 0.12\))

94.8 (\(\pm 0.06\))

0.658 (\(\pm 0.000\))

  1. Bolded values represent best top-N accuracies and best MRR across both GLN and RetroSim (including their individually re-ranked versions)