Lista de obras - O Anatole von Lilienfeld

Ab initio molecular dynamics calculations of ion hydration free energies

artículo científico publicado en 2009

Accurate ab initio energy gradients in chemical compound space

artículo científico publicado en 2009

Alchemical Normal Modes Unify Chemical Space

artículo científico publicado en 2018

Alchemical Predictions for Computational Catalysis: Potential and Limitations

artículo científico publicado en 2017

Alchemical Variations of Intermolecular Energies According to Molecular Grand-Canonical Ensemble Density Functional Theory

artículo científico publicado en 2007

Alchemical derivatives of reaction energetics ⬇️

artículo científico publicado el 28 de agosto de 2010

Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies

artículo científico publicado en 2013

Atoms in Molecules from Alchemical Perturbation Density Functional Theory

scientific article published on 14 November 2019

Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach

artículo científico publicado en 2015

Blind test of density-functional-based methods on intermolecular interaction energies

artículo científico publicado en 2016

Boosting Quantum Machine Learning Models with a Multilevel Combination Technique: Pople Diagrams Revisited

scientific article published on 12 February 2019

Coarse-grained interaction potentials for polyaromatic hydrocarbons

artículo científico publicado en 2006

Collective many-body van der Waals interactions in molecular systems ⬇️

artículo científico publicado el 24 de agosto de 2012

Communication: Understanding molecular representations in machine learning: The role of uniqueness and target similarity. ⬇️

artículo científico publicado en 2016

Data enhanced Hammett-equation: reaction barriers in chemical space

artículo científico publicado en 2020

Effects of perturbation order and basis set on alchemical predictions

artículo científico publicado en 2020

Electronic spectra from TDDFT and machine learning in chemical space ⬇️

artículo científico publicado en 2015

Encrypted machine learning of molecular quantum properties

artículo científico publicado en 2023

Enol Tautomers of Watson−Crick Base Pair Models Are Metastable Because of Nuclear Quantum Effects ⬇️

artículo científico publicado el 25 de agosto de 2010

Exploring dissociative water adsorption on isoelectronically BN doped graphene using alchemical derivatives

artículo científico publicado en 2017

FCHL revisited: Faster and more accurate quantum machine learning

artículo científico publicado en 2020

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

artículo científico publicado en 2012

Generalized Density-Functional Tight-Binding Repulsive Potentials from Unsupervised Machine Learning.

artículo científico publicado en 2018

Genetic Optimization of Training Sets for Improved Machine Learning Models of Molecular Properties

artículo científico publicado en 2017

Guiding ab initio calculations by alchemical derivatives

artículo científico publicado en 2016

Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space

artículo científico publicado en 2015

Machine Learning of Parameters for Accurate Semiempirical Quantum Chemical Calculations

artículo científico publicado en 2015

Machine learning meets volcano plots: computational discovery of cross-coupling catalysts

scholarly article by Benjamin Meyer et al published 21 September 2018 in Chemical Science

Machine learning of molecular electronic properties in chemical compound space

article

Many Molecular Properties from One Kernel in Chemical Space

artículo científico publicado en 2015

Modeling of molecular atomization energies using machine learning.

artículo científico publicado en 2012

Molecular grand-canonical ensemble density functional theory and exploration of chemical space

artículo científico publicado en 2006

Operators in quantum machine learning: Response properties in chemical space

scientific article published on 01 February 2019

Path Integral Computation of Quantum Free Energy Differences Due to Alchemical Transformations Involving Mass and Potential

artículo científico publicado en 2011

Predicting noncovalent interactions between aromatic biomolecules with London-dispersion-corrected DFT.

artículo científico publicado en 2007

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

artículo científico publicado en 2017

Properties and reactivity of nucleic acids relevant to epigenomics, transcriptomics, and therapeutics

artículo científico publicado en 2016

Quantum chemistry structures and properties of 134 kilo molecules

artículo científico publicado en 2014

Quantum machine learning in chemical compound space.

artículo científico publicado en 2017

Quantum machine learning using atom-in-molecule-based fragments selected on the fly

scientific article published on 14 September 2020

Quantum-chemistry-aided identification, synthesis and experimental validation of model systems for conformationally controlled reaction studies: separation of the conformers of 2,3-dibromobuta-1,3-diene in the gas phase

artículo científico publicado en 2020

Retrospective on a decade of machine learning for chemical discovery

artículo científico publicado en 2020

Ruppet al.Reply:

artículo científico publicado en 2012

Torsional Potentials of Glyoxal, Oxalyl Halides, and Their Thiocarbonyl Derivatives: Challenges for Popular Density Functional Approximations

artículo científico publicado en 2018

Toward Quantitative Structure-Property Relationships for Charge Transfer Rates of Polycyclic Aromatic Hydrocarbons

artículo científico publicado en 2011

Toward transferable interatomic van der Waals interactions without electrons: the role of multipole electrostatics and many-body dispersion ⬇️

artículo científico publicado en 2014

Transferable Atomic Multipole Machine Learning Models for Small Organic Molecules. ⬇️

artículo científico publicado en 2015

Two- and three-body interatomic dispersion energy contributions to binding in molecules and solids

artículo científico publicado en 2010

Variational optimization of effective atom centered potentials for molecular properties

artículo científico publicado en 2005

Lista de obras de O Anatole von Lilienfeld

Ab initio molecular dynamics calculations of ion hydration free energies

Accurate ab initio energy gradients in chemical compound space

Alchemical Normal Modes Unify Chemical Space

Alchemical Predictions for Computational Catalysis: Potential and Limitations

Alchemical Variations of Intermolecular Energies According to Molecular Grand-Canonical Ensemble Density Functional Theory

Alchemical derivatives of reaction energetics ⬇️

Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies

Atoms in Molecules from Alchemical Perturbation Density Functional Theory

Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach

Blind test of density-functional-based methods on intermolecular interaction energies

Boosting Quantum Machine Learning Models with a Multilevel Combination Technique: Pople Diagrams Revisited

Coarse-grained interaction potentials for polyaromatic hydrocarbons

Collective many-body van der Waals interactions in molecular systems ⬇️

Communication: Understanding molecular representations in machine learning: The role of uniqueness and target similarity. ⬇️

Data enhanced Hammett-equation: reaction barriers in chemical space

Effects of perturbation order and basis set on alchemical predictions

Electronic spectra from TDDFT and machine learning in chemical space ⬇️

Encrypted machine learning of molecular quantum properties

Enol Tautomers of Watson−Crick Base Pair Models Are Metastable Because of Nuclear Quantum Effects ⬇️

Exploring dissociative water adsorption on isoelectronically BN doped graphene using alchemical derivatives

FCHL revisited: Faster and more accurate quantum machine learning

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

Generalized Density-Functional Tight-Binding Repulsive Potentials from Unsupervised Machine Learning.

Genetic Optimization of Training Sets for Improved Machine Learning Models of Molecular Properties

Guiding ab initio calculations by alchemical derivatives

Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space

Machine Learning of Parameters for Accurate Semiempirical Quantum Chemical Calculations

Machine learning meets volcano plots: computational discovery of cross-coupling catalysts

Machine learning of molecular electronic properties in chemical compound space

Many Molecular Properties from One Kernel in Chemical Space

Modeling of molecular atomization energies using machine learning.

Molecular grand-canonical ensemble density functional theory and exploration of chemical space

Operators in quantum machine learning: Response properties in chemical space

Path Integral Computation of Quantum Free Energy Differences Due to Alchemical Transformations Involving Mass and Potential

Predicting noncovalent interactions between aromatic biomolecules with London-dispersion-corrected DFT.

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

Properties and reactivity of nucleic acids relevant to epigenomics, transcriptomics, and therapeutics

Quantum chemistry structures and properties of 134 kilo molecules

Quantum machine learning in chemical compound space.

Quantum machine learning using atom-in-molecule-based fragments selected on the fly

Quantum-chemistry-aided identification, synthesis and experimental validation of model systems for conformationally controlled reaction studies: separation of the conformers of 2,3-dibromobuta-1,3-diene in the gas phase

Retrospective on a decade of machine learning for chemical discovery

Ruppet al.Reply:

Torsional Potentials of Glyoxal, Oxalyl Halides, and Their Thiocarbonyl Derivatives: Challenges for Popular Density Functional Approximations

Toward Quantitative Structure-Property Relationships for Charge Transfer Rates of Polycyclic Aromatic Hydrocarbons

Toward transferable interatomic van der Waals interactions without electrons: the role of multipole electrostatics and many-body dispersion ⬇️

Transferable Atomic Multipole Machine Learning Models for Small Organic Molecules. ⬇️

Two- and three-body interatomic dispersion energy contributions to binding in molecules and solids

Variational optimization of effective atom centered potentials for molecular properties