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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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Transformer for Reaction Informatics – utilizing PyTorch Lightning

Esbenbjerrum/ April 24, 2021

In the last blogpost I covered how LSTM-to-LSTM networks could be used to “translate” reactants into products of chemical reactions. Performance was however not very good 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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Building a simple SMILES based QSAR model with LSTM cells in PyTorch

Esbenbjerrum/ June 6, 2020

Last blog-post I showed how to use PyTorch to build a feed forward neural network model for molecular property prediction (QSAR: Quantitative structure-activity relationship). RDKit was used

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Building a simple QSAR model using a feed forward neural network in PyTorch

Esbenbjerrum/ May 1, 2020

In my previous blogposts I’ve entirely been using Keras for my neural networks. Keras as a stand-alone is now no longer active developed, but are instead now

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Master your molecule generator 2. Direct steering of conditional recurrent neural networks (cRNNs)

Esbenbjerrum/ November 12, 2019

Long time ago in a GPU far-far away, the deep learning rebels are happy. They have created new ways of working with chemistry using deep learning technology

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Learn how to make a jupyter notebook widget for annotation of atom properties

Esbenbjerrum/ September 28, 2019

  Not so long ago Greg Landrum published a blog post with an example of how the SVG rendering from RDKit in a jupyter notebook can be

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Never do these mistakes when comparing regression models

Esbenbjerrum/ August 25, 2019

Some time ago I stumbled upon some work by Patrick Walters which shows that correlation coefficients have a rather large standard error when the sample sets sizes

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rdEditor: An open-source molecular editor based using Python, PySide2 and RDKit

Esben Jannik Bjerrum/ March 30, 2019

At the RDKit UGM 2018 in Cambridge I made a lightning talk where I show cased rdEditor.  I’ve wanted to write a bit about it for some

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