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FCHL revisited: Faster and more accurate quantum machine learning

The Journal of chemical physics, 2020-01, Vol.152 (4), p.044107-044107

2020

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Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error

Journal of chemical theory and computation, 2017-11, Vol.13 (11), p.5255-5264

2017

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Predictive Minisci late stage functionalization with transfer learning

Nature communications, 2024-01, Vol.15 (1), p.426-13, Article 426

2024

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Machine Learning Energies of 2 Million Elpasolite (ABC_{2}D_{6}) Crystals

Physical review letters, 2016-09, Vol.117 (13), p.135502-135502, Article 135502

2016

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Alchemical and structural distribution based representation for universal quantum machine learning

The Journal of chemical physics, 2018-06, Vol.148 (24), p.241717-241717

2018

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Operators in quantum machine learning: Response properties in chemical space

The Journal of chemical physics, 2019-02, Vol.150 (6), p.064105-064105

2019

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GPU-accelerated approximate kernel method for quantum machine learning

The Journal of chemical physics, 2022-12, Vol.157 (21), p.214801-214801

2022

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BenchML: an extensible pipelining framework for benchmarking representations of materials and molecules at scale

Machine learning: science and technology, 2022-12, Vol.3 (4), p.40501

2022

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An assessment of the structural resolution of various fingerprints commonly used in machine learning

Machine learning: science and technology, 2021-03, Vol.2 (1), p.15018

2021

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Rapid discovery of stable materials by coordinate-free coarse graining

Science advances, 2022-07, Vol.8 (30), p.eabn4117

2022

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Identifying crystal structures beyond known prototypes from x-ray powder diffraction spectra

Physical review materials, 2024-10, Vol.8 (10), Article 103801

2024

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Machine Learning Energies of 2 Million Elpasolite (ABC sub(2)D sub(6)) Crystals

Physical review letters, 2016-09, Vol.117 (13)

2016

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Neural networks and kernel ridge regression for excited states dynamics of CH 2 NH 2+ : From single-state to multi-state representations and multi-property machine learning models

Machine learning: science and technology, 2020-06, Vol.1 (2), p.25009

2020

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Neural networks and kernel ridge regression for excited states dynamics of CH2NH: From single-state to multi-state representations and multi-property machine learning models

Machine learning: science and technology, 2020-06, Vol.1 (2)

2020

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Neural networks and kernel ridge regression for excited states dynamics of CH2NH 2+: From single-state to multi-state representations and multi-property machine learning models

Machine learning: science and technology, 2020-05, Vol.1 (2)

2020

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Modeling Materials Quantum Properties with Machine Learning

Materials Informatics, 2019

2019

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Crystal structure representations for machine learning models of formation energies

International journal of quantum chemistry, 2015-08, Vol.115 (16), p.1094-1101

2015

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The landing(s) of Philae and inferences about comet surface mechanical properties

Science (American Association for the Advancement of Science), 2015-07, Vol.349 (6247), p.494-494

2015

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Predictions Of Heart Rate And Oxygen Uptake During Exercise From Kinetics By Randomized Work Rate Changes: 314

Medicine and science in sports and exercise, 2021-08, Vol.53 (8S), p.98-98

2021

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Switching from vitamin K antagonists to direct oral anticoagulants in non‐valvular atrial fibrillation patients: Does low time in therapeutic range affect persistence?

Journal of thrombosis and haemostasis, 2022-02, Vol.20 (2), p.339-352

2022

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Using a 3D asymmetry index as a novel form for capturing complex three-dimensionality in positional plagiocephaly

Scientific reports, 2022-12, Vol.12 (1), p.20831-20831, Article 20831

2022

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Dynamic cell tracking using time-lapse MRI with variable temporal resolution Cartesian sampling

Magnetic resonance in medicine, 2023-12, Vol.90 (6), p.2443-2453

2023

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A Non-Isothermal Pore Network Model of Primary Freeze Drying

Pharmaceutics, 2023-08, Vol.15 (8), p.2131

2023

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Pore-scale study of coupled heat and mass transfer during primary freeze-drying using an irregular pore network model

Drying technology, 2024-10, p.1-21

2024

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Stable fixation using absorbable sutures in craniofacial surgery in patients over 24 months of age—a retrospective study

Child's nervous system, 2024-08, Vol.40 (8), p.2545-2550

2024

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FCHL revisited: Faster and more accurate quantum machine learning

Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error

Predictive Minisci late stage functionalization with transfer learning

Machine Learning Energies of 2 Million Elpasolite (ABC_{2}D_{6}) Crystals

Alchemical and structural distribution based representation for universal quantum machine learning

Operators in quantum machine learning: Response properties in chemical space

GPU-accelerated approximate kernel method for quantum machine learning

BenchML: an extensible pipelining framework for benchmarking representations of materials and molecules at scale

An assessment of the structural resolution of various fingerprints commonly used in machine learning

Rapid discovery of stable materials by coordinate-free coarse graining

Identifying crystal structures beyond known prototypes from x-ray powder diffraction spectra

Machine Learning Energies of 2 Million Elpasolite (ABC sub(2)D sub(6)) Crystals

Neural networks and kernel ridge regression for excited states dynamics of CH 2 NH 2+ : From single-state to multi-state representations and multi-property machine learning models

Neural networks and kernel ridge regression for excited states dynamics of CH2NH: From single-state to multi-state representations and multi-property machine learning models

Neural networks and kernel ridge regression for excited states dynamics of CH2NH 2+: From single-state to multi-state representations and multi-property machine learning models

Modeling Materials Quantum Properties with Machine Learning

Crystal structure representations for machine learning models of formation energies

The landing(s) of Philae and inferences about comet surface mechanical properties

Predictions Of Heart Rate And Oxygen Uptake During Exercise From Kinetics By Randomized Work Rate Changes: 314

Switching from vitamin K antagonists to direct oral anticoagulants in non‐valvular atrial fibrillation patients: Does low time in therapeutic range affect persistence?

Using a 3D asymmetry index as a novel form for capturing complex three-dimensionality in positional plagiocephaly

Dynamic cell tracking using time-lapse MRI with variable temporal resolution Cartesian sampling

A Non-Isothermal Pore Network Model of Primary Freeze Drying

Pore-scale study of coupled heat and mass transfer during primary freeze-drying using an irregular pore network model

Stable fixation using absorbable sutures in craniofacial surgery in patients over 24 months of age—a retrospective study

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