论文标题
使用图形自动编码器的分子连续表示
Continuous Representation of Molecules Using Graph Variational Autoencoder
论文作者
论文摘要
为了连续代表分子，我们提出了一种以VAE形式的生成模型，该模型在分子的2D-graph结构上运行。采用侧面预测器来修剪潜在空间，并帮助解码器产生有意义的分子张量。除了在药物设计和财产预测中的潜在适用性外，我们还基于基于基于RNN的编码器和解码器的其他类似方法的其他类似方法来显示该技术的出色性能。
In order to continuously represent molecules, we propose a generative model in the form of a VAE which is operating on the 2D-graph structure of molecules. A side predictor is employed to prune the latent space and help the decoder in generating meaningful adjacency tensor of molecules. Other than the potential applicability in drug design and property prediction, we show the superior performance of this technique in comparison to other similar methods based on the SMILES representation of the molecules with RNN based encoder and decoder.
