Esben Jannik Bjerrum

According to our database, Esben Jannik Bjerrum authored at least 29 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Metis: a python-based user interface to collect expert feedback for generative chemistry models.

Janosch Menke, Yasmine Nahal, Esben Jannik Bjerrum, Mikhail Kabeshov, Samuel Kaski, Ola Engkvist

J. Cheminformatics, December, 2024

2023

Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES.

Esben Jannik Bjerrum, Christian Margreitter, Thomas Blaschke, Simona Kolarova, Raquel Lopez-Rios de Castro

J. Comput. Aided Mol. Des., August, 2023

2022

Chemformer: a pre-trained transformer for computational chemistry.

Ross Irwin, Spyridon Dimitriadis, Jiazhen He, Esben Jannik Bjerrum

Mach. Learn. Sci. Technol., 2022

Fast prediction of distances between synthetic routes with deep learning.

Samuel Genheden, Ola Engkvist, Esben Jannik Bjerrum

Mach. Learn. Sci. Technol., 2022

Exploring Graph Traversal Algorithms in Graph-Based Molecular Generation.

Rocío Mercado, Esben Jannik Bjerrum, Ola Engkvist

J. Chem. Inf. Model., 2022

LibINVENT: Reaction-based Generative Scaffold Decoration for <i>in Silico</i> Library Design.

Vendy Fialková, Jiaxi Zhao, Kostas Papadopoulos, Ola Engkvist, Esben Jannik Bjerrum, Thierry Kogej, Atanas Patronov

J. Chem. Inf. Model., 2022

Human-in-the-loop assisted de novo molecular design.

Iiris Sundin, Alexey Voronov, Haoping Xiao, Kostas Papadopoulos, Esben Jannik Bjerrum, Markus Heinonen, Atanas Patronov, Samuel Kaski, Ola Engkvist

J. Cheminformatics, 2022

Transformer-based molecular optimization beyond matched molecular pairs.

Jiazhen He, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Atanas Patronov, Esben Jannik Bjerrum, Ola Engkvist

J. Cheminformatics, 2022

Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES.

Esben Jannik Bjerrum, Christian Margreitter, Thomas Blaschke, Raquel Lopez-Rios de Castro

CoRR, 2022

Autonomous Drug Design with Multi-Armed Bandits.

Hampus Gummesson Svensson, Esben Jannik Bjerrum, Christian Tyrchan, Ola Engkvist, Morteza Haghir Chehreghani

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Graph networks for molecular design.

Rocío Mercado, Tobias Rastemo, Edvard Lindelöf, Günter Klambauer, Ola Engkvist, Hongming Chen, Esben Jannik Bjerrum

Mach. Learn. Sci. Technol., 2021

Artificial applicability labels for improving policies in retrosynthesis prediction.

Esben Jannik Bjerrum, Amol Thakkar, Ola Engkvist

Mach. Learn. Sci. Technol., 2021

Clustering of Synthetic Routes Using Tree Edit Distance.

Samuel Genheden, Ola Engkvist, Esben Jannik Bjerrum

J. Chem. Inf. Model., 2021

Molecular optimization by capturing chemist's intuition using deep neural networks.

Jiazhen He, Huifang You, Emil Sandström, Eva Nittinger, Esben Jannik Bjerrum, Christian Tyrchan, Werngard Czechtizky, Ola Engkvist

J. Cheminformatics, 2021

2020

Direct steering of de novo molecular generation with descriptor conditional recurrent neural networks.

Panagiotis-Christos Kotsias, Josep Arús-Pous, Hongming Chen, Ola Engkvist, Christian Tyrchan, Esben Jannik Bjerrum

Nat. Mach. Intell., 2020

AiZynthFinder: a fast, robust and flexible open-source software for retrosynthetic planning.

Samuel Genheden, Amol Thakkar, Veronika Chadimová, Jean-Louis Reymond, Ola Engkvist, Esben Jannik Bjerrum

J. Cheminformatics, 2020

SMILES-based deep generative scaffold decorator for de-novo drug design.

Josep Arús-Pous, Atanas Patronov, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist

J. Cheminformatics, 2020

2019

De Novo Molecular Design by Combining Deep Autoencoder Recurrent Neural Networks with Generative Topographic Mapping.

Boris Sattarov, Igor I. Baskin, Dragos Horvath, Gilles Marcou, Esben Jannik Bjerrum, Alexandre Varnek

J. Chem. Inf. Model., 2019

A de novo molecular generation method using latent vector based generative adversarial network.

Oleksii Prykhodko, Simon Johansson, Panagiotis-Christos Kotsias, Josep Arús-Pous, Esben Jannik Bjerrum, Ola Engkvist, Hongming Chen

J. Cheminformatics, 2019

Randomized SMILES strings improve the quality of molecular generative models.

Josep Arús-Pous, Simon Johansson, Oleksii Prykhodko, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist

J. Cheminformatics, 2019

Neural Network Guided Tree-Search Policies for Synthesis Planning.

Amol Thakkar, Esben Jannik Bjerrum, Ola Engkvist, Jean-Louis Reymond

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, 2019

Improving Deep Generative Models with Randomized SMILES.

Josep Arús-Pous, Simon Johansson, Oleksii Prykhodko, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, 2019

2018

Improving Chemical Autoencoder Latent Space and Molecular De novo Generation Diversity with Heteroencoders.

Esben Jannik Bjerrum

CoRR, 2018

2017

pICalculax: Improved Prediction of Isoelectric Point for Modified Peptides.

Esben Jannik Bjerrum, Jan H. Jensen, Jakob L. Tolborg

J. Chem. Inf. Model., August, 2017

DeepIEP: a Peptide Sequence Model of Isoelectric Point (IEP/pI) using Recurrent Neural Networks (RNNs).

Esben Jannik Bjerrum

CoRR, 2017

Data Augmentation of Spectral Data for Convolutional Neural Network (CNN) Based Deep Chemometrics.

Esben Jannik Bjerrum, Mads Glahder, Thomas Skov

CoRR, 2017

Molecular Generation with Recurrent Neural Networks (RNNs).

Esben Jannik Bjerrum, Richard Threlfall

CoRR, 2017

SMILES Enumeration as Data Augmentation for Neural Network Modeling of Molecules.

Esben Jannik Bjerrum

CoRR, 2017

2016

Machine learning optimization of cross docking accuracy.

Esben Jannik Bjerrum

Comput. Biol. Chem., 2016