Datasets include the structures, MOB energy features and MOB dipole features for QM9, four series of peptides, water and fourteen small molecules. HF and correlation energies and the corresponding dipole moments computed at MP2/cc-pVTZ theory are also included. Files are under embargo until the associated paper is publishedRelated Publication: Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-orbital-based Machine Learning arXiv 2022-05-31 https://doi.org/10.48550/arXiv.2205.15510 engFiles available via S3 at ://renc.osn.xsede.org/ini210004tommorrell/0_D1.20142/challenge_dataset.zip 1.54 GB Download README.md 0.0 GB Download ...
Supplementary data for Manuscript: Challenges in protein QM/MM simulations with intra-backbone link ...
Molecular dipole moment in liquid water is an intriguing property, partly due to the fact that there...
We investigate the impact of choosing regressors and molecular representations for the construction ...
This study extends the accurate and transferable molecular-orbital-based machine learning (MOB-ML) a...
Geometries and Dipole Moments calculated by B3LYP/6-31G(d,p) for 10071 Organic Molecular Structures....
The molecular dipole moment (mu) is a central quantity in chemistry. It is essential in predicting i...
Additional file 1: Figure S1. Graphical representation of the DFT-DM vs. a) DMNBO and b) DMPEOE for ...
268 pagesIn this thesis, I will discuss six projects that I participated in during my Ph.D. study, w...
MOB-ML features, HF energies, pair correlation energies, and geometries. Data are provided for water...
We investigate the impact of choosing regressors and molecular representations for the construction ...
Molecular-orbital-based machine learning (MOB-ML) provides a general framework for the prediction of...
The predictive accuracy of Machine Learning (ML) models of molecular properties depends on the choic...
Accurate representation of the molecular electrostatic potential, which is often expanded in distrib...
In recent years, machine learning (ML) methods have become increasingly popular in computational che...
This repo contains the structures, HF and MRCI+Q energies, and MOB features for MOB-ML (KA-GPR) of C...
Supplementary data for Manuscript: Challenges in protein QM/MM simulations with intra-backbone link ...
Molecular dipole moment in liquid water is an intriguing property, partly due to the fact that there...
We investigate the impact of choosing regressors and molecular representations for the construction ...
This study extends the accurate and transferable molecular-orbital-based machine learning (MOB-ML) a...
Geometries and Dipole Moments calculated by B3LYP/6-31G(d,p) for 10071 Organic Molecular Structures....
The molecular dipole moment (mu) is a central quantity in chemistry. It is essential in predicting i...
Additional file 1: Figure S1. Graphical representation of the DFT-DM vs. a) DMNBO and b) DMPEOE for ...
268 pagesIn this thesis, I will discuss six projects that I participated in during my Ph.D. study, w...
MOB-ML features, HF energies, pair correlation energies, and geometries. Data are provided for water...
We investigate the impact of choosing regressors and molecular representations for the construction ...
Molecular-orbital-based machine learning (MOB-ML) provides a general framework for the prediction of...
The predictive accuracy of Machine Learning (ML) models of molecular properties depends on the choic...
Accurate representation of the molecular electrostatic potential, which is often expanded in distrib...
In recent years, machine learning (ML) methods have become increasingly popular in computational che...
This repo contains the structures, HF and MRCI+Q energies, and MOB features for MOB-ML (KA-GPR) of C...
Supplementary data for Manuscript: Challenges in protein QM/MM simulations with intra-backbone link ...
Molecular dipole moment in liquid water is an intriguing property, partly due to the fact that there...
We investigate the impact of choosing regressors and molecular representations for the construction ...