Hierarchical visualization of materials space with graph convolutional neural networks
出版年份 2018 全文链接
标题
Hierarchical visualization of materials space with graph convolutional neural networks
作者
关键词
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出版物
JOURNAL OF CHEMICAL PHYSICS
Volume 149, Issue 17, Pages 174111
出版商
AIP Publishing
发表日期
2018-11-07
DOI
10.1063/1.5047803
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- SchNet – A deep learning architecture for molecules and materials
- (2018) K. T. Schütt et al. JOURNAL OF CHEMICAL PHYSICS
- Alchemical and structural distribution based representation for universal quantum machine learning
- (2018) Felix A. Faber et al. JOURNAL OF CHEMICAL PHYSICS
- Data-Driven Learning of Total and Local Energies in Elemental Boron
- (2018) Volker L. Deringer et al. PHYSICAL REVIEW LETTERS
- Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties
- (2018) Tian Xie et al. PHYSICAL REVIEW LETTERS
- Learning atoms for materials discovery
- (2018) Quan Zhou et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Machine learning for the structure–energy–property landscapes of molecular crystals
- (2018) Félix Musil et al. Chemical Science
- MoleculeNet: a benchmark for molecular machine learning
- (2018) Zhenqin Wu et al. Chemical Science
- Mapping uncharted territory in ice from zeolite networks to ice structures
- (2018) Edgar A. Engel et al. Nature Communications
- Quantum-chemical insights from deep tensor neural networks
- (2017) Kristof T. Schütt et al. Nature Communications
- Universal fragment descriptors for predicting properties of inorganic crystals
- (2017) Olexandr Isayev et al. Nature Communications
- 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
- Molecular graph convolutions: moving beyond fingerprints
- (2016) Steven Kearnes et al. JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
- Machine Learning Force Fields: Construction, Validation, and Outlook
- (2016) V. Botu et al. Journal of Physical Chemistry C
- Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach
- (2016) Rafael Gómez-Bombarelli et al. NATURE MATERIALS
- Comparing molecules and solids across structural and alchemical space
- (2016) Sandip De et al. PHYSICAL CHEMISTRY CHEMICAL PHYSICS
- Machine Learning Energies of 2 Million Elpasolite(ABC2D6)Crystals
- (2016) Felix A. Faber et al. PHYSICAL REVIEW LETTERS
- A general-purpose machine learning framework for predicting properties of inorganic materials
- (2016) Logan Ward et al. npj Computational Materials
- Materials Cartography: Representing and Mining Materials Space Using Structural and Electronic Fingerprints
- (2015) Olexandr Isayev et al. CHEMISTRY OF MATERIALS
- 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
- Prediction of Low-Thermal-Conductivity Compounds with First-Principles Anharmonic Lattice-Dynamics Calculations and Bayesian Optimization
- (2015) Atsuto Seko et al. PHYSICAL REVIEW LETTERS
- Big Data of Materials Science: Critical Role of the Descriptor
- (2015) Luca M. Ghiringhelli et al. PHYSICAL REVIEW LETTERS
- Review of recent progress in chemical stability of perovskite solar cells
- (2015) Guangda Niu et al. Journal of Materials Chemistry A
- Observation of an all-boron fullerene
- (2014) Hua-Jin Zhai et al. Nature Chemistry
- How to represent crystal structures for machine learning: Towards fast prediction of electronic properties
- (2014) K. T. Schütt et al. PHYSICAL REVIEW B
- Combinatorial screening for new materials in unconstrained composition space with machine learning
- (2014) B. Meredig et al. PHYSICAL REVIEW B
- Progress, Challenges, and Opportunities in Two-Dimensional Materials Beyond Graphene
- (2013) Sheneve Z. Butler et al. ACS Nano
- 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
- β-Rhombohedral Boron: At the Crossroads of the Chemistry of Boron and the Physics of Frustration
- (2013) Tadashi Ogitsu et al. CHEMICAL REVIEWS
- Graphene-Like Two-Dimensional Materials
- (2013) Mingsheng Xu et al. CHEMICAL REVIEWS
- Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD)
- (2013) James E. Saal et al. JOM
- Metrics for measuring distances in configuration spaces
- (2013) Ali Sadeghi et al. JOURNAL OF CHEMICAL PHYSICS
- Perovskites: The Emergence of a New Era for Low-Cost, High-Efficiency Solar Cells
- (2013) Henry J. Snaith Journal of Physical Chemistry Letters
- 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
- Accelerating materials property predictions using machine learning
- (2013) Ghanshyam Pilania et al. Scientific Reports
- Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
- (2013) Anubhav Jain et al. APL Materials
- Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis
- (2012) Shyue Ping Ong et al. COMPUTATIONAL MATERIALS SCIENCE
- New cubic perovskites for one- and two-photon water splitting using the computational materials repository
- (2012) Ivano E. Castelli et al. Energy & Environmental Science
- Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
- (2012) Matthias Rupp et al. PHYSICAL REVIEW LETTERS
- Computational screening of perovskite metal oxides for optimal solar light capture
- (2011) Ivano E. Castelli et al. Energy & Environmental Science
- Metadynamics in the conformational space nonlinearly dimensionally reduced by Isomap
- (2011) Vojtěch Spiwok et al. JOURNAL OF CHEMICAL PHYSICS
- Atom-centered symmetry functions for constructing high-dimensional neural network potentials
- (2011) Jörg Behler JOURNAL OF 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
- Combinatorial and High-Throughput Screening of Materials Libraries: Review of State of the Art
- (2011) Radislav Potyrailo et al. ACS Combinatorial Science
- Finding Nature’s Missing Ternary Oxide Compounds Using Machine Learning and Density Functional Theory
- (2010) Geoffroy Hautier et al. CHEMISTRY OF MATERIALS
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