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Esben Jannik Bjerrum
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2020 – today
- 2024
- [j20]Janosch Menke
, Yasmine Nahal, Esben Jannik Bjerrum, Mikhail Kabeshov, Samuel Kaski, Ola Engkvist:
Metis: a python-based user interface to collect expert feedback for generative chemistry models. J. Cheminformatics 16(1): 100 (2024) - 2023
- [j19]Esben Jannik Bjerrum, Christian Margreitter
Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES. J. Comput. Aided Mol. Des. 37(8): 373-394 (2023) - 2022
- [j18]Jiazhen He
Transformer-based molecular optimization beyond matched molecular pairs. J. Cheminformatics 14(1): 18 (2022) - [j17]Iiris Sundin
Human-in-the-loop assisted de novo molecular design. J. Cheminformatics 14(1): 86 (2022) - [j16]Vendy Fialková, Jiaxi Zhao, Kostas Papadopoulos
LibINVENT: Reaction-based Generative Scaffold Decoration for in Silico Library Design. J. Chem. Inf. Model. 62(9): 2046-2063 (2022) - [j15]Rocío Mercado, Esben Jannik Bjerrum
Exploring Graph Traversal Algorithms in Graph-Based Molecular Generation. J. Chem. Inf. Model. 62(9): 2093-2100 (2022) - [j14]Samuel Genheden
Fast prediction of distances between synthetic routes with deep learning. Mach. Learn. Sci. Technol. 3(1): 15018 (2022) - [j13]Ross Irwin, Spyridon Dimitriadis, Jiazhen He, Esben Jannik Bjerrum
Chemformer: a pre-trained transformer for computational chemistry. Mach. Learn. Sci. Technol. 3(1): 15022 (2022) - [c3]Hampus Gummesson Svensson, Esben Jannik Bjerrum, Christian Tyrchan, Ola Engkvist, Morteza Haghir Chehreghani:
Autonomous Drug Design with Multi-Armed Bandits. IEEE Big Data 2022: 5584-5592 - [i7]Hampus Gummesson Svensson, Esben Jannik Bjerrum, Christian Tyrchan, Ola Engkvist, Morteza Haghir Chehreghani:
Autonomous Drug Design with Multi-armed Bandits. CoRR abs/2207.01393 (2022) - [i6]Esben Jannik Bjerrum, Christian Margreitter, Thomas Blaschke, Raquel Lopez-Rios de Castro:
Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES. CoRR abs/2210.12458 (2022) - 2021
- [j12]Jiazhen He
Molecular optimization by capturing chemist's intuition using deep neural networks. J. Cheminformatics 13(1): 26 (2021) - [j11]Samuel Genheden
Clustering of Synthetic Routes Using Tree Edit Distance. J. Chem. Inf. Model. 61(8): 3899-3907 (2021) - [j10]Esben Jannik Bjerrum
Artificial applicability labels for improving policies in retrosynthesis prediction. Mach. Learn. Sci. Technol. 2(1): 17001 (2021) - [j9]Rocío Mercado
Graph networks for molecular design. Mach. Learn. Sci. Technol. 2(2): 25023 (2021) - 2020
- [j8]Josep Arús-Pous
SMILES-based deep generative scaffold decorator for de-novo drug design. J. Cheminformatics 12(1): 38 (2020) - [j7]Samuel Genheden
AiZynthFinder: a fast, robust and flexible open-source software for retrosynthetic planning. J. Cheminformatics 12(1): 70 (2020) - [j6]Panagiotis-Christos Kotsias
Direct steering of de novo molecular generation with descriptor conditional recurrent neural networks. Nat. Mach. Intell. 2(5): 254-265 (2020)
2010 – 2019
- 2019
- [j5]Josep Arús-Pous
Randomized SMILES strings improve the quality of molecular generative models. J. Cheminformatics 11(1): 71:1-71:13 (2019) - [j4]Oleksii Prykhodko, Simon Johansson
A de novo molecular generation method using latent vector based generative adversarial network. J. Cheminformatics 11(1): 74 (2019) - [j3]Boris Sattarov
De Novo Molecular Design by Combining Deep Autoencoder Recurrent Neural Networks with Generative Topographic Mapping. J. Chem. Inf. Model. 59(3): 1182-1196 (2019) - [c2]Amol Thakkar, Esben Jannik Bjerrum, Ola Engkvist
Neural Network Guided Tree-Search Policies for Synthesis Planning. ICANN (Workshop) 2019: 721-724 - [c1]Josep Arús-Pous
Improving Deep Generative Models with Randomized SMILES. ICANN (Workshop) 2019: 747-751 - 2018
- [i5]Esben Jannik Bjerrum
Improving Chemical Autoencoder Latent Space and Molecular De novo Generation Diversity with Heteroencoders. CoRR abs/1806.09300 (2018) - 2017
- [j2]Esben Jannik Bjerrum
pICalculax: Improved Prediction of Isoelectric Point for Modified Peptides. J. Chem. Inf. Model. 57(8): 1723-1727 (2017) - [i4]Esben Jannik Bjerrum
SMILES Enumeration as Data Augmentation for Neural Network Modeling of Molecules. CoRR abs/1703.07076 (2017) - [i3]Esben Jannik Bjerrum
Molecular Generation with Recurrent Neural Networks (RNNs). CoRR abs/1705.04612 (2017) - [i2]Esben Jannik Bjerrum
Data Augmentation of Spectral Data for Convolutional Neural Network (CNN) Based Deep Chemometrics. CoRR abs/1710.01927 (2017) - [i1]Esben Jannik Bjerrum
DeepIEP: a Peptide Sequence Model of Isoelectric Point (IEP/pI) using Recurrent Neural Networks (RNNs). CoRR abs/1712.09553 (2017) - 2016
- [j1]Esben Jannik Bjerrum
Machine learning optimization of cross docking accuracy. Comput. Biol. Chem. 62: 133-144 (2016)
Coauthor Index
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