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Theoretical and Computational Chemistry

Working Paper

Evaluation of Reinforcement Learning in Transformer-based Molecular Design

Jiazhen He, Alessandro Tibo, Jon Paul Janet, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Ola Engkvist

Version 2 posted 10 July 2024

705

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Theoretical and Computational Chemistry

Working Paper

Chemformer: A Pre-Trained Transformer for Computational Chemistry

Ross Irwin, Spyridon Dimitriadis, Jiazhen He, Esben Bjerrum

Version 1 posted 15 July 2021

5,629

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1

Citations

Theoretical and Computational Chemistry

Working Paper

Transformer Neural Network for Structure Constrained Molecular Optimization

Jiazhen He, Felix Mattsson, Marcus Forsberg, Esben Jannik Bjerrum, Ola Engkvist, eva nittinger, Christian Tyrchan, Werngard Czechtizky

Version 1 posted 15 April 2021

968

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4

Citations

Theoretical and Computational Chemistry

Working Paper

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

Version 2 posted 29 October 2020

1,966

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1

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Theoretical and Computational Chemistry

Working Paper

Levenshtein Augmentation Improves Performance of SMILES Based Deep-Learning Synthesis Prediction

Dean Sumner, Jiazhen He, Amol Thakkar, Ola Engkvist, Esben Jannik Bjerrum

Version 2 posted 06 July 2020

1,115

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2

Citations

Theoretical and Computational Chemistry

Working Paper

REINVENT4: Modern AI–Driven Generative Molecule Design

Hannes Loeffler, Jiazhen He, Alessandro Tibo, Jon Paul Janet, Alexey Voronov, Lewis Mervin, Ola Engkvist

Version 1 posted 06 November 2023

7,402

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7

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Theoretical and Computational Chemistry

Review

Exhaustive local chemical space exploration using a transformer model

Alessandro Tibo, Jiazhen He, Jon Paul Janet, Eva Nittinger, Ola Engkvist

Version 2 posted 22 May 2024

1,588

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Theoretical and Computational Chemistry

Working Paper

Transformer Neural Network-Based Molecular Optimization Using General Transformations

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

Version 1 posted 18 November 2021

821

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Refine Search

8 results in Jiazhen He in Authors: Jiazhen He

Evaluation of Reinforcement Learning in Transformer-based Molecular Design

Chemformer: A Pre-Trained Transformer for Computational Chemistry

Transformer Neural Network for Structure Constrained Molecular Optimization

Molecular Optimization by Capturing Chemist’s Intuition Using Deep Neural Networks

Levenshtein Augmentation Improves Performance of SMILES Based Deep-Learning Synthesis Prediction

REINVENT4: Modern AI–Driven Generative Molecule Design

Exhaustive local chemical space exploration using a transformer model

Transformer Neural Network-Based Molecular Optimization Using General Transformations

8 results in Authors: Jiazhen He