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Popelier, Paul L. A.
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1

Probing Non-Covalent Interactions through Molecular Balance..:

Falcioni, Fabio ; Bennett, Sophie ; Stroer-Jarvis, Pallas.
Molecules.  29 (2024)  5 - p. 1043 , 2024
Link: https://doi.org/10.3390/..
 
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2

An Unsupervised Machine Learning Approach for the Automatic..:

Gallegos, Miguel ; Isamura, Bienfait Kabuyaya ; Popelier, Paul L. A..
Journal of Chemical Information and Modeling.  64 (2024)  8 - p. 3059-3079 , 2024
Link: https://doi.org/10.1021/..
 
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3

Transferability of Buckingham Parameters for Short-Range Re..:

Chung, Jaiming J. K. ; Brown, Matthew L. ; Popelier, Paul L. A.
The Journal of Physical Chemistry A.  128 (2024)  22 - p. 4561-4572 , 2024
Link: https://doi.org/10.1021/..
 
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4

Determining the Factors Accounting for Reaction Selectivity..:

Cador, Aël ; Morell, Christophe ; Tognetti, Vincent..
ChemPhysChem.  , 2024
Link: https://doi.org/10.1002/..
 
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5

Incorporating Noncovalent Interactions in Transfer Learning..:

Brown, Matthew L. ; Isamura, Bienfait K. ; Skelton, Jonathan M..
Journal of Chemical Theory and Computation.  20 (2024)  14 - p. 5994-6008 , 2024
Link: https://doi.org/10.1021/..
 
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6

FFLUX molecular simulations driven by atomic Gaussian proce..:

Manchev, Yulian T. ; Popelier, Paul L. A.
Journal of Computational Chemistry.  45 (2024)  15 - p. 1235-1246 , 2024
Link: https://doi.org/10.1002/..
 
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7

Calibration of uncertainty in the active learning of machin..:

Thomas-Mitchell, Adam ; Hawe, Glenn ; Popelier, Paul L A
Machine Learning: Science and Technology.  4 (2023)  4 - p. 045034 , 2023
Link: https://doi.org/10.1088/..
 
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8

Metaheuristic optimisation of Gaussian process regression m..:

Isamura, Bienfait K. ; Popelier, Paul L.A.
Artificial Intelligence Chemistry.  1 (2023)  2 - p. 100021 , 2023
Link: https://doi.org/10.1016/..
 
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9

IQA analysis of the two-particle density matrix: chemical i..:

Vincent, Mark A. ; Popelier, Paul L. A.
Theoretical Chemistry Accounts.  142 (2023)  11 - p. , 2023
Link: https://doi.org/10.1007/..
 
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10

Gaussian Process Regression Models for Predicting Atomic En..:

Burn, Matthew J. ; Popelier, Paul L. A.
Journal of Chemical Theory and Computation.  19 (2023)  4 - p. 1370-1380 , 2023
Link: https://doi.org/10.1021/..
 
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11

Application of the FFLUX Force Field to Molecular Crystals:..:

Brown, Matthew L. ; Skelton, Jonathan M. ; Popelier, Paul L. A.
Journal of Chemical Theory and Computation.  19 (2023)  21 - p. 7946-7959 , 2023
Link: https://doi.org/10.1021/..
 
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12

Interacting Quantum Atoms and Multipolar Electrostatic Stud..:

Triestram, Lena ; Falcioni, Fabio ; Popelier, Paul L. A.
ACS Omega.  8 (2023)  38 - p. 34844-34851 , 2023
Link: https://doi.org/10.1021/..
 
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13

How to Compute Atomistic Insight in DFT Clusters: The REG-I..:

Falcioni, Fabio ; Popelier, Paul L. A.
Journal of Chemical Information and Modeling.  63 (2023)  14 - p. 4312-4327 , 2023
Link: https://doi.org/10.1021/..
 
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14

FEREBUS: a high-performance modern Gaussian process regress..:

Burn, Matthew J. ; Popelier, Paul L. A.
Digital Discovery.  2 (2023)  1 - p. 152-164 , 2023
Link: https://doi.org/10.1039/..
 
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15

Construction of a Gaussian Process Regression Model of Form..:

Brown, Matthew L. ; Skelton, Jonathan M. ; Popelier, Paul L. A.
The Journal of Physical Chemistry A.  127 (2023)  7 - p. 1702-1714 , 2023
Link: https://doi.org/10.1021/..
 
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