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Black-Box Optimization for Automated Discovery

Accounts of chemical research, 2021-03, Vol.54 (6), p.1334-1346

2021

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ChemTS: an efficient python library for de novo molecular generation

Science and technology of advanced materials, 2017-12, Vol.18 (1), p.972-976

2017

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Designing Nanostructures for Phonon Transport via Bayesian Optimization

Physical review. X, 2017-05, Vol.7 (2), p.021024, Article 021024

2017

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Machine-Learning-Assisted Development and Theoretical Consideration for the Al2Fe3Si3 Thermoelectric Material

ACS applied materials & interfaces, 2019-03, Vol.11 (12), p.11545-11554

2019

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Structure prediction of boron-doped graphene by machine learning

The Journal of chemical physics, 2018-06, Vol.148 (24), p.241716-241716

2018

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Molecular generation by Fast Assembly of (Deep)SMILES fragments

Journal of cheminformatics, 2021-11, Vol.13 (1), p.88-88, Article 88

2021

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Leveraging algorithmic search in quantum chemical reaction path finding

Physical chemistry chemical physics : PCCP, 2022-05, Vol.24 (17), p.135-131

2022

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Data-driven approach for the prediction and interpretation of core-electron loss spectroscopy

Scientific reports, 2018-09, Vol.8 (1), p.13548-12, Article 13548

2018

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Differentiable optimization layers enhance GNN-based mitosis detection

Scientific reports, 2023-08, Vol.13 (1), p.14306-14306, Article 14306

2023

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Machine learning-driven optimization in powder manufacturing of Ni-Co based superalloy

Materials & design, 2021-01, Vol.198, p.109290, Article 109290

2021

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COMBO: An efficient Bayesian optimization library for materials science

Materials discovery, 2016-06, Vol.4, p.18-21

2016

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Sparse modeling of EELS and EDX spectral imaging data by nonnegative matrix factorization

Ultramicroscopy, 2016-11, Vol.170, p.43-59

2016

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Hunting for Organic Molecules with Artificial Intelligence: Molecules Optimized for Desired Excitation Energies

ACS central science, 2018-09, Vol.4 (9), p.1126-1133

2018

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Using molecular dynamics simulations to prioritize and understand AI-generated cell penetrating peptides

Scientific reports, 2021-05, Vol.11 (1), p.10630-10630, Article 10630

2021

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CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data

BMC bioinformatics, 2016-09, Vol.17 (1), p.363-363, Article 363

2016

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Fe–Al–Si Thermoelectric (FAST) Materials and Modules: Diffusion Couple and Machine-Learning-Assisted Materials Development

ACS applied materials & interfaces, 2021-11, Vol.13 (45), p.53346-53354

2021

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Crystal structure prediction accelerated by Bayesian optimization

Physical review materials, 2018-01, Vol.2 (1), Article 013803

2018

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Optimization of a Heterogeneous Ternary Li3PO4–Li3BO3–Li2SO4 Mixture for Li-Ion Conductivity by Machine Learning

Journal of physical chemistry. C, 2020-06, Vol.124 (24), p.12865-12870

2020

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Application of Bayesian Optimization for Pharmaceutical Product Development

Journal of pharmaceutical innovation, 2020-09, Vol.15 (3), p.333-343

2020

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An interpretable machine learning model for diagnosis of Alzheimer's disease

PeerJ (San Francisco, CA), 2019-03, Vol.7, p.e6543-e6543, Article e6543

2019

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Vision-based egg quality prediction in Pacific bluefin tuna (Thunnus orientalis) by deep neural network

Scientific reports, 2021-01, Vol.11 (1), p.6-6, Article 6

2021

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Ultranarrow-Band Wavelength-Selective Thermal Emission with Aperiodic Multilayered Metamaterials Designed by Bayesian Optimization

ACS central science, 2019-02, Vol.5 (2), p.319-326

2019

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Machine-Learning-Guided Library Design Cycle for Directed Evolution of Enzymes: The Effects of Training Data Composition on Sequence Space Exploration

ACS catalysis, 2021-12, Vol.11 (23), p.14615-14624

2021

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Acceleration of stable interface structure searching using a kriging approach

Japanese Journal of Applied Physics, 2016-04, Vol.55 (4), p.45502

2016

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Artificial Neural Networks Applied as Molecular Wave Function Solvers

Journal of chemical theory and computation, 2020-06, Vol.16 (6), p.3513-3529

2020

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Black-Box Optimization for Automated Discovery

ChemTS: an efficient python library for de novo molecular generation

Designing Nanostructures for Phonon Transport via Bayesian Optimization

Machine-Learning-Assisted Development and Theoretical Consideration for the Al2Fe3Si3 Thermoelectric Material

Structure prediction of boron-doped graphene by machine learning

Molecular generation by Fast Assembly of (Deep)SMILES fragments

Leveraging algorithmic search in quantum chemical reaction path finding

Data-driven approach for the prediction and interpretation of core-electron loss spectroscopy

Differentiable optimization layers enhance GNN-based mitosis detection

Machine learning-driven optimization in powder manufacturing of Ni-Co based superalloy

COMBO: An efficient Bayesian optimization library for materials science

Sparse modeling of EELS and EDX spectral imaging data by nonnegative matrix factorization

Hunting for Organic Molecules with Artificial Intelligence: Molecules Optimized for Desired Excitation Energies

Using molecular dynamics simulations to prioritize and understand AI-generated cell penetrating peptides

CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data

Fe–Al–Si Thermoelectric (FAST) Materials and Modules: Diffusion Couple and Machine-Learning-Assisted Materials Development

Crystal structure prediction accelerated by Bayesian optimization

Optimization of a Heterogeneous Ternary Li3PO4–Li3BO3–Li2SO4 Mixture for Li-Ion Conductivity by Machine Learning

Application of Bayesian Optimization for Pharmaceutical Product Development

An interpretable machine learning model for diagnosis of Alzheimer's disease

Vision-based egg quality prediction in Pacific bluefin tuna (Thunnus orientalis) by deep neural network

Ultranarrow-Band Wavelength-Selective Thermal Emission with Aperiodic Multilayered Metamaterials Designed by Bayesian Optimization

Machine-Learning-Guided Library Design Cycle for Directed Evolution of Enzymes: The Effects of Training Data Composition on Sequence Space Exploration

Acceleration of stable interface structure searching using a kriging approach

Artificial Neural Networks Applied as Molecular Wave Function Solvers

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