This repository contains the source code for SGPT-RL, a tool for chemical design using generative pre-trained transformer and deep reinforcement learning. Through employing GPT model as the policy network, SGPT-RL can learn scaffold patterns in exploring the chemical space. Publication: TBA Files included in this release: charlesxu90/sgpt-v1.2.zip: the source code of SGPT-RL. Source code repository: https://github.com/charlesxu90/sgp
Molecular design is a critical aspect of various scientific and industrial fields, where the propert...
Contains code to reproduce published results as well as links to the molecules generated in this wor...
Training data and code accompanying paper on "Automated patent extraction powers generative modeling...
This repository contains the code and data for SGPT-RL, a tool for chemical design using transformer...
This repository contains the code and data for SGPT-RL, a tool for chemical design using transformer...
This repository contains the data for SGPT-RL, a tool for chemical design using generative pre-train...
This repository contains the code and data for SGPT-RL, a tool for chemical design using transformer...
Molecular discovery seeks to generate chemical species tailored to very specific needs. In this pape...
Geometry optimization is a crucial step in computational chemistry, and the efficiency of optimizati...
Trained Transformer model as described and used in the publication of " Molecular optimization by ca...
This work introduces a method to tune a sequence-based generative model for molecular de novo design...
Abstract In recent years, the field of computational drug design has made significant strides in the...
During the last decade, there is an increasing interest in applying deep learning in de novo drug de...
Code base for paper "Reinforcement learning prioritizes general applicability in reaction optimizati...
The number of 'small' molecules that may be of interest to chemical biologists - chemical space - is...
Molecular design is a critical aspect of various scientific and industrial fields, where the propert...
Contains code to reproduce published results as well as links to the molecules generated in this wor...
Training data and code accompanying paper on "Automated patent extraction powers generative modeling...
This repository contains the code and data for SGPT-RL, a tool for chemical design using transformer...
This repository contains the code and data for SGPT-RL, a tool for chemical design using transformer...
This repository contains the data for SGPT-RL, a tool for chemical design using generative pre-train...
This repository contains the code and data for SGPT-RL, a tool for chemical design using transformer...
Molecular discovery seeks to generate chemical species tailored to very specific needs. In this pape...
Geometry optimization is a crucial step in computational chemistry, and the efficiency of optimizati...
Trained Transformer model as described and used in the publication of " Molecular optimization by ca...
This work introduces a method to tune a sequence-based generative model for molecular de novo design...
Abstract In recent years, the field of computational drug design has made significant strides in the...
During the last decade, there is an increasing interest in applying deep learning in de novo drug de...
Code base for paper "Reinforcement learning prioritizes general applicability in reaction optimizati...
The number of 'small' molecules that may be of interest to chemical biologists - chemical space - is...
Molecular design is a critical aspect of various scientific and industrial fields, where the propert...
Contains code to reproduce published results as well as links to the molecules generated in this wor...
Training data and code accompanying paper on "Automated patent extraction powers generative modeling...