All SMILES Variational Autoencoder

30 May 2019Zaccary AlpersteinArtem CherkasovJason Tyler Rolfe

Variational autoencoders (VAEs) defined over SMILES string and graph-based representations of molecules promise to improve the optimization of molecular properties, thereby revolutionizing the pharmaceuticals and materials industries. However, these VAEs are hindered by the non-unique nature of SMILES strings and the computational cost of graph convolutions... (read more)

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Evaluation results from the paper


Task Dataset Model Metric name Metric value Global rank Compare
Drug Discovery Tox21 SSVAE with multiple SMILES AUC 0.875 # 1