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Cheminformania

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    • Esben Jannik Bjerrum
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  • About
    • About Cheminformania
    • Esben Jannik Bjerrum

Non-conditional De Novo molecular Generation with Transformer Encoders

Esbenbjerrum/ May 13, 2021

We’ve known since 2016 that LSTM networks can be used to generate novel and valid SMILES strings of novel molecules after being trained on a dataset of

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Deep Learning Reaction Prediction with PyTorch

Esbenbjerrum/ March 29, 2021

In this blogpost I’ll show how to predict chemical reactions with a sequence to sequence network based on LSTM cells. It’s the same principle as IBM’s RXN

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Using GraphINVENT to generate novel DRD2 actives

Esbenbjerrum/ November 2, 2020

I have been writing a lot about how to use SMILES together with deep learning architectures such as RNNs and LSTM networks to perform various cheminformatic and

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