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Table 5 Prediction performance of logS and logD tasks based on embedding extracted from VAEs jointly trained with several descriptors

From: Improving VAE based molecular representations for compound property prediction

Task

Descriptors

Classifier

1D ResNet

R2/RMSE

MLP

R2/RMSE

LR

R2/RMSE

logS

MolLogP

0.790/0.926

0.770/0.971

0.751/1.010

MolLogP, PEOE_VSA6

0.809/0.88

0.769/0.970

0.752/1.006

logP, PEOE_VSA6, MolWt

0.804/0.896

0.771/0.967

0.762/0.986

logD

MolLogP

0.520 / 0.840

0.319 / 1.001

0.296 / 1.018

MolLogP, NumAromaticRings

0.522 / 0.839

0.335/0.989

0.295/1.019

MolLogP, NumAromaticRings,

RingCount

0.510/ 0.851

0.303/1.013

0.277/1.032

  1. Bold values indicate the best performance over all models