Kavli Affiliate: Wei Gao
| First 5 Authors: Li Kai, Li Ning, Zhang Wei, Gao Ming,
| Summary:
Based on the traditional VAE, a novel neural network model is presented, with
the latest molecular representation, SELFIES, to improve the effect of
generating new molecules. In this model, multi-layer convolutional network and
Fisher information are added to the original encoding layer to learn the data
characteristics and guide the encoding process, which makes the features of the
data hiding layer more aggregated, and integrates the Long Short Term Memory
neural network (LSTM) into the decoding layer for better data generation, which
effectively solves the degradation phenomenon generated by the encoding layer
and decoding layer of the original VAE model. Through experiments on zinc
molecular data sets, it is found that the similarity in the new VAE is 8.47%
higher than that of the original ones. SELFIES are better at generating a
variety of molecules than the traditional molecular representation, SELFIES.
Experiments have shown that using SELFIES and the new VAE model presented in
this paper can improve the effectiveness of generating new molecules.
| Search Query: ArXiv Query: search_query=au:”Wei Gao”&id_list=&start=0&max_results=10