Скачать или смотреть Tiago Sousa- Combining Evolutionary Algorithms w/ generative models towards focused molecular design

AUTHORS: Tiago Sousa, João Correia, Vítor Pereira and Miguel Rocha

PAPER TITLE: Combining Multi-objective Evolutionary Algorithms with deep generative models towards focused molecular design

SESSION CHAIRS: Francisco Fernandez De Vega and Pablo García Sánchez

ABSTRACT: Recent advances in applying deep generative learning to molecular design have led to a large number of novel approaches to the targeted generation of molecules towards specific features and applications. In this work, we expand on the latent space navigation approach, where molecules are optimized by operating in their latent representation inside a deep auto-encoder, by introducing multi-objective evolutionary algorithms (MOEAs) and benchmarking the proposed framework on several objectives from recent literature. By using several case studies from literature, we show that our proposed method is capable of controlling abstract chemical properties, is competitive with other state-of-the-art methods and is also able to perform relevant tasks such as optimizing a predefined molecule while maintaining a similarity threshold. Also, MOEAs allow to generate molecules with a good level of diversity, which is a desired feature.

Find the full paper here: https://link.springer.com/chapter/10....