Unsupervised machine learning in atomistic simulations, between predictions and understanding

Accurate molecular polarizabilities with coupled cluster theory and machine learning

(2019) David M. Wilkins et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Atom-density representations for machine learning

(2019) Michael J. Willatt et al.   JOURNAL OF CHEMICAL PHYSICS

Quantum Machine Learning in Chemical Compound Space

(2018) O. Anatole von Lilienfeld   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Large-Scale Computational Screening of Molecular Organic Semiconductors Using Crystal Structure Prediction

(2018) Jack Yang et al.   CHEMISTRY OF MATERIALS

Comparison of permutationally invariant polynomials, neural networks, and Gaussian approximation potentials in representing water interactions through many-body expansions

(2018) Thuong T. Nguyen et al.   JOURNAL OF CHEMICAL PHYSICS

Automatic selection of atomic fingerprints and reference configurations for machine-learning potentials

(2018) Giulio Imbalzano et al.   JOURNAL OF CHEMICAL PHYSICS

Recognizing Local and Global Structural Motifs at the Atomic Scale

(2018) Piero Gasparotto et al.   Journal of Chemical Theory and Computation

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

(2018) Julian J. Kranz et al.   Journal of Chemical Theory and Computation

GAtor: A First-Principles Genetic Algorithm for Molecular Crystal Structure Prediction

(2018) Farren Curtis et al.   Journal of Chemical Theory and Computation

Two-dimensional materials from high-throughput computational exfoliation of experimentally known compounds

(2018) Nicolas Mounet et al.   Nature Nanotechnology

Symmetry-Adapted Machine Learning for Tensorial Properties of Atomistic Systems

(2018) Andrea Grisafi et al.   PHYSICAL REVIEW LETTERS

Automated crystal characterization with a fast neighborhood graph analysis method

(2018) Wesley F. Reinhart et al.   Soft Matter

Machine learning for the structure–energy–property landscapes of molecular crystals

(2018) Félix Musil et al.   Chemical Science

Modeling lithium-ion solid-state electrolytes with a pinball model

(2018) Leonid Kahle et al.   PHYSICAL REVIEW MATERIALS

Machine learning for molecular and materials science

(2018) Keith T. Butler et al.   NATURE

Predicting polymorphism in molecular crystals using orientational entropy

(2018) Pablo M. Piaggi et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

SISSO: A compressed-sensing method for identifying the best low-dimensional descriptor in an immensity of offered candidates

(2018) Runhai Ouyang et al.   PHYSICAL REVIEW MATERIALS

Generalized convex hull construction for materials discovery

(2018) Andrea Anelli et al.   PHYSICAL REVIEW MATERIALS

Stochastic Neural Network Approach for Learning High-Dimensional Free Energy Surfaces

(2017) Elia Schneider et al.   PHYSICAL REVIEW LETTERS

Intrinsic map dynamics exploration for uncharted effective free-energy landscapes

(2017) Eliodoro Chiavazzo et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost

(2017) J. S. Smith et al.   Chemical Science

Heterogeneity in homogeneous nucleation from billion-atom molecular dynamics simulation of solidification of pure metal

(2017) Yasushi Shibuta et al.   Nature Communications

Mapping and classifying molecules from a high-throughput structural database

(2017) Sandip De et al.   Journal of Cheminformatics

Algorithms for hierarchical clustering: an overview, II

(2017) Fionn Murtagh et al.   Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery

Machine learning unifies the modeling of materials and molecules

(2017) Albert P. Bartók et al.   Science Advances

Machine learning in materials informatics: recent applications and prospects

(2017) Rampi Ramprasad et al.   npj Computational Materials

Assessing Local Structure Motifs Using Order Parameters for Motif Recognition, Interstitial Identification, and Diffusion Path Characterization

(2017) Nils E. R. Zimmermann et al.   Frontiers in Materials

AiiDA: automated interactive infrastructure and database for computational science

(2016) Giovanni Pizzi et al.   COMPUTATIONAL MATERIALS SCIENCE

A fingerprint based metric for measuring similarities of crystalline structures

(2016) Li Zhu et al.   JOURNAL OF CHEMICAL PHYSICS

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

(2016) Bing Huang et al.   JOURNAL OF CHEMICAL PHYSICS

Perspective: Machine learning potentials for atomistic simulations

(2016) Jörg Behler   JOURNAL OF CHEMICAL PHYSICS

Exploration, Sampling, And Reconstruction of Free Energy Surfaces with Gaussian Process Regression

(2016) Letif Mones et al.   Journal of Chemical Theory and Computation

Comparing molecules and solids across structural and alchemical space

(2016) Sandip De et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Spectral gap optimization of order parameters for sampling complex molecular systems

(2016) Pratyush Tiwary et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Materials Cartography: Representing and Mining Materials Space Using Structural and Electronic Fingerprints

(2015) Olexandr Isayev et al.   CHEMISTRY OF MATERIALS

Gaussian approximation potentials: A brief tutorial introduction

(2015) Albert P. Bartók et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Crystal structure representations for machine learning models of formation energies

(2015) Felix Faber et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Systematic comparison of crystalline and amorphous phases: Charting the landscape of water structures and transformations

(2015) Fabio Pietrucci et al.   JOURNAL OF CHEMICAL PHYSICS

Machine learning of single molecule free energy surfaces and the impact of chemistry and environment upon structure and dynamics

(2015) Rachael A. Mansbach et al.   JOURNAL OF CHEMICAL PHYSICS

Accelerated materials property predictions and design using motif-based fingerprints

(2015) Tran Doan Huan et al.   PHYSICAL REVIEW B

Locating landmarks on high-dimensional free energy surfaces

(2015) Ming Chen et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Markov state models of biomolecular conformational dynamics

(2014) John D Chodera et al.   CURRENT OPINION IN STRUCTURAL BIOLOGY

Recognizing molecular patterns by machine learning: An agnostic structural definition of the hydrogen bond

(2014) Piero Gasparotto et al.   JOURNAL OF CHEMICAL PHYSICS

Free Energy Surface Reconstruction from Umbrella Samples Using Gaussian Process Regression

(2014) Thomas Stecher et al.   Journal of Chemical Theory and Computation

Fast recovery of free energy landscapes via diffusion-map-directed molecular dynamics

(2014) Jordane Preto et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

How to represent crystal structures for machine learning: Towards fast prediction of electronic properties

(2014) K. T. Schütt et al.   PHYSICAL REVIEW B

Clustering by fast search and find of density peaks

(2014) A. Rodriguez et al.   SCIENCE

Discovering Mountain Passes via Torchlight: Methods for the Definition of Reaction Coordinates and Pathways in Complex Macromolecular Reactions

(2013) Mary A. Rohrdanz et al.   Annual Review of Physical Chemistry

Metrics for measuring distances in configuration spaces

(2013) Ali Sadeghi et al.   JOURNAL OF CHEMICAL PHYSICS

Identification of slow molecular order parameters for Markov model construction

(2013) Guillermo Pérez-Hernández et al.   JOURNAL OF CHEMICAL PHYSICS

Demonstrating the Transferability and the Descriptive Power of Sketch-Map

(2013) Michele Ceriotti et al.   Journal of Chemical Theory and Computation

The high-throughput highway to computational materials design

(2013) Stefano Curtarolo et al.   NATURE MATERIALS

On representing chemical environments

(2013) Albert P. Bartók et al.   PHYSICAL REVIEW B

From Metadynamics to Dynamics

(2013) Pratyush Tiwary et al.   PHYSICAL REVIEW LETTERS

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

(2013) Anubhav Jain et al.   APL Materials

Nonlinear dimensionality reduction and mapping of compound libraries for drug discovery

(2012) Michael Reutlinger et al.   JOURNAL OF MOLECULAR GRAPHICS & MODELLING

Automated identification and indexing of dislocations in crystal interfaces

(2012) Alexander Stukowski et al.   MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

(2012) Matthias Rupp et al.   PHYSICAL REVIEW LETTERS

Using sketch-map coordinates to analyze and bias molecular dynamics simulations

(2012) G. A. Tribello et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Metadynamics in the conformational space nonlinearly dimensionally reduced by Isomap

(2011) Vojtěch Spiwok et al.   JOURNAL OF CHEMICAL PHYSICS

Determination of reaction coordinates via locally scaled diffusion map

(2011) Mary A. Rohrdanz et al.   JOURNAL OF CHEMICAL PHYSICS

A chirality-based metrics for free-energy calculations in biomolecular systems

(2011) Adriana Pietropaolo et al.   JOURNAL OF COMPUTATIONAL CHEMISTRY

Delineation of Folding Pathways of a β-Sheet Miniprotein

(2011) Wenwei Zheng et al.   JOURNAL OF PHYSICAL CHEMISTRY B

Ab initiorandom structure searching

(2011) Chris J Pickard et al.   JOURNAL OF PHYSICS-CONDENSED MATTER

Neural network potential-energy surfaces in chemistry: a tool for large-scale simulations

(2011) Jörg Behler   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Graph Theory MeetsAb InitioMolecular Dynamics: Atomic Structures and Transformations at the Nanoscale

(2011) Fabio Pietrucci et al.   PHYSICAL REVIEW LETTERS

Simplifying the representation of complex free-energy landscapes using sketch-map

(2011) Michele Ceriotti et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

The inefficiency of re-weighted sampling and the curse of system size in high-order path integration

(2011) M. Ceriotti et al.   PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

Crystal structure prediction using the minima hopping method

(2010) Maximilian Amsler et al.   JOURNAL OF CHEMICAL PHYSICS

Everything you wanted to know about Markov State Models but were afraid to ask

(2010) Vijay S. Pande et al.   METHODS

Solid-liquid interface free energy through metadynamics simulations

(2010) Stefano Angioletti-Uberti et al.   PHYSICAL REVIEW B

Systematic determination of order parameters for chain dynamics using diffusion maps

(2010) A. L. Ferguson et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Automatic identification and representation of protein binding sites for molecular docking

(2010) Jim Ruppert et al.   PROTEIN SCIENCE

Permutationally invariant potential energy surfaces in high dimensionality

(2009) Bastiaan J. Braams et al.   INTERNATIONAL REVIEWS IN PHYSICAL CHEMISTRY

A Collective Variable for the Efficient Exploration of Protein Beta-Sheet Structures: Application to SH3 and GB1

(2009) Fabio Pietrucci et al.   Journal of Chemical Theory and Computation

Efficient and Direct Generation of Multidimensional Free Energy Surfaces via Adiabatic Dynamics without Coordinate Transformations

(2008) Jerry B. Abrams et al.   JOURNAL OF PHYSICAL CHEMISTRY B

Metadynamics: a method to simulate rare events and reconstruct the free energy in biophysics, chemistry and material science

(2008) Alessandro Laio et al.   REPORTS ON PROGRESS IN PHYSICS