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10/04/2021
Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation
Recently, utilizing reinforcement learning (RL) to generate molecules wi...
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06/12/2020
A benchmark study on reliable molecular supervised learning via Bayesian learning
Virtual screening aims to find desirable compounds from chemical library...
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03/17/2020
A comprehensive study on the prediction reliability of graph neural networks for virtual screening
Prediction models based on deep neural networks are increasingly gaining...
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04/17/2019
Predicting drug-target interaction using 3D structure-embedded graph representations from graph neural networks
Accurate prediction of drug-target interaction (DTI) is essential for in...
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03/20/2019
Uncertainty quantification of molecular property prediction with Bayesian neural networks
Deep neural networks have outperformed existing machine learning models ...
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06/15/2018
Molecular generative model based on conditional variational autoencoder for de novo molecular design
We propose a molecular generative model based on the conditional variati...
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05/28/2018