Application of Curriculum Learning for de novo design of small molecules

Examensarbete för masterexamen

Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12380/302731
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Type: Examensarbete för masterexamen
Title: Application of Curriculum Learning for de novo design of small molecules
Authors: Arango, Juan Diego
Abstract: In recent years, Deep Learning has given new energy to the field of de novo design. This field is the generation of novel chemical compound ideas, which can be used for new applications. AstraZeneca has developed software for this task called REINVENT. The software uses Reinforcement Learning and a user-defined scoring function to create new compound ideas. The objective of this work is to implement, within REINVENT, the technique of Curriculum Learning. Here, the scoring function during the training phase is actively modified. Besides the implementation, this work explores how this approach improves performance compared to the classical Reinforcement Learning approach.
Issue Date: 2021
Publisher: Chalmers tekniska högskola / Institutionen för fysik
URI: https://hdl.handle.net/20.500.12380/302731
Collection:Examensarbeten för masterexamen // Master Theses



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