Related references
Note: Only part of the references are listed.Applicability Domain Based on Ensemble Learning in Classification and Regression Analyses
Hiromasa Kaneko et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2014)
Applicability Domain Analysis (ADAN): A Robust Method for Assessing the Reliability of Drug Property Predictions
Pau Carrio et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2014)
Perspective: Fifty years of density-functional theory in chemical physics
Axel D. Becke
JOURNAL OF CHEMICAL PHYSICS (2014)
Designing rules and probabilistic weighting for fast materials discovery in the Perovskite structure
I. E. Castelli et al.
MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING (2014)
Proposed definition of crystal substructure and substructural similarity
Lusann Yang et al.
PHYSICAL REVIEW B (2014)
How to represent crystal structures for machine learning: Towards fast prediction of electronic properties
K. T. Schuett et al.
PHYSICAL REVIEW B (2014)
Rational design of all organic polymer dielectrics
Vinit Sharma et al.
NATURE COMMUNICATIONS (2014)
On-the-fly machine-learning for high-throughput experiments: search for rare-earth-free permanent magnets
Aaron Gilad Kusne et al.
SCIENTIFIC REPORTS (2014)
Using Random Forest To Model the Domain Applicability of Another Random Forest Model
Robert P. Sheridan
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2013)
Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies
Katja Hansen et al.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION (2013)
Machine learning of molecular electronic properties in chemical compound space
Gregoire Montavon et al.
NEW JOURNAL OF PHYSICS (2013)
On representing chemical environments
Albert P. Bartok et al.
PHYSICAL REVIEW B (2013)
The Stuff of Dreams
Gerbrand Ceder et al.
SCIENTIFIC AMERICAN (2013)
Property Phase Diagrams for Compound Semiconductors through Data Mining
Srikant Srinivasan et al.
MATERIALS (2013)
Accelerating materials property predictions using machine learning
Ghanshyam Pilania et al.
SCIENTIFIC REPORTS (2013)
Density functional theory in materials science
Joerg Neugebauer et al.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE (2013)
Sorting Stable versus Unstable Hypothetical Compounds: The Case of Multi-Functional ABX Half-Heusler Filled Tetrahedral Structures
Xiuwen Zhang et al.
ADVANCED FUNCTIONAL MATERIALS (2012)
From the computer to the laboratory: materials discovery and design using first-principles calculations
Geoffroy Hautier et al.
JOURNAL OF MATERIALS SCIENCE (2012)
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
Matthias Rupp et al.
PHYSICAL REVIEW LETTERS (2012)
Data-Driven Model for Estimation of Friction Coefficient Via Informatics Methods
Eric W. Bucholz et al.
TRIBOLOGY LETTERS (2012)
Novel approaches to multiscale modelling in materials science
J. A. Elliott
INTERNATIONAL MATERIALS REVIEWS (2011)
Atom-centered symmetry functions for constructing high-dimensional neural network potentials
Joerg Behler
JOURNAL OF CHEMICAL PHYSICS (2011)
Neural network potential-energy surfaces in chemistry: a tool for large-scale simulations
Joerg Behler
PHYSICAL CHEMISTRY CHEMICAL PHYSICS (2011)
Identifying the 'inorganic gene' for high-temperature piezoelectric perovskites through statistical learning
Prasanna V. Balachandran et al.
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES (2011)
Finding Nature's Missing Ternary Oxide Compounds Using Machine Learning and Density Functional Theory
Geoffroy Hautier et al.
CHEMISTRY OF MATERIALS (2010)
Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons
Albert P. Bartok et al.
PHYSICAL REVIEW LETTERS (2010)
Evolutionary Crystal Structure Prediction as a Method for the Discovery of Minerals and Materials
Artem R. Oganov et al.
THEORETICAL AND COMPUTATIONAL METHODS IN MINERAL PHYSICS: GEOPHYSICAL APPLICATIONS (2010)
Kernel methods in machine learning
Thomas Hofmann et al.
ANNALS OF STATISTICS (2008)
Metadynamics: a method to simulate rare events and reconstruct the free energy in biophysics, chemistry and material science
Alessandro Laio et al.
REPORTS ON PROGRESS IN PHYSICS (2008)
Rapid structural mapping of ternary metallic alloy systems using the combinatorial approach and cluster analysis
C. J. Long et al.
REVIEW OF SCIENTIFIC INSTRUMENTS (2007)
An overview of spatial microscopic and accelerated kinetic Monte Carlo methods
Abhijit Chatterjee et al.
JOURNAL OF COMPUTER-AIDED MATERIALS DESIGN (2007)
Predicting crystal structure by merging data mining with quantum mechanics
Christopher C. Fischer et al.
NATURE MATERIALS (2006)
High-throughput and data mining with ab initio methods
D Morgan et al.
MEASUREMENT SCIENCE AND TECHNOLOGY (2005)
Accelerated molecular dynamics: A promising and efficient simulation method for biomolecules
D Hamelberg et al.
JOURNAL OF CHEMICAL PHYSICS (2004)
Minima hopping: An efficient search method for the global minimum of the potential energy surface of complex molecular systems
S Goedecker
JOURNAL OF CHEMICAL PHYSICS (2004)
Escaping free-energy minima
A Laio et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2002)
Long time scale kinetic Monte Carlo simulations without lattice approximation and predefined event table
G Henkelman et al.
JOURNAL OF CHEMICAL PHYSICS (2001)
An introduction to kernel-based learning algorithms
KR Müller et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2001)
Temperature-accelerated dynamics for simulation of infrequent events
MR Sorensen et al.
JOURNAL OF CHEMICAL PHYSICS (2000)