Polymer Genome: A Polymer Informatics Platform to Accelerate Polymer Discovery (English)
- New search for: Chandrasekaran, Anand
- New search for: Kim, Chiho
- New search for: Ramprasad, Rampi
- New search for: Schütt, Kristof T.
- New search for: Chmiela, Stefan
- New search for: von Lilienfeld, O. Anatole
- New search for: Tkatchenko, Alexandre
- New search for: Tsuda, Koji
- New search for: Müller, Klaus-Robert
- Further information on Müller, Klaus-Robert:
- https://orcid.org/https://orcid.org/0000-0002-3861-7685
- New search for: Chandrasekaran, Anand
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In:
Machine Learning Meets Quantum Physics
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Chapter: 18
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397-412
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2020
- Article/Chapter (Book) / Electronic Resource
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Title:Polymer Genome: A Polymer Informatics Platform to Accelerate Polymer Discovery
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Additional title:Lect Notes Phys
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Contributors:Schütt, Kristof T. ( editor ) / Chmiela, Stefan ( editor ) / von Lilienfeld, O. Anatole ( editor ) / Tkatchenko, Alexandre ( editor ) / Tsuda, Koji ( editor ) / Müller, Klaus-Robert ( editor ) / Chandrasekaran, Anand ( author ) / Kim, Chiho ( author ) / Ramprasad, Rampi ( author )
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Published in:Machine Learning Meets Quantum Physics ; Chapter: 18 ; 397-412Lecture Notes in Physics ; 968 ; 397-412
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Publisher:
- New search for: Springer International Publishing
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Place of publication:Cham
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Publication date:2020-06-04
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Size:16 pages
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ISBN:
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ISSN:
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DOI:
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Type of media:Article/Chapter (Book)
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Type of material:Electronic Resource
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Language:English
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Keywords:
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Source:
Table of contents eBook
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 1
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IntroductionSchütt, Kristof T. / Chmiela, Stefan / von Lilienfeld, O. Anatole / Tkatchenko, Alexandre / Tsuda, Koji / Müller, Klaus-Robert et al. | 2020
- 2
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Introduction to Material ModelingHermann, Jan et al. | 2020
- 3
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Kernel Methods for Quantum ChemistryPronobis, Wiktor / Müller, Klaus-Robert et al. | 2020
- 4
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Introduction to Neural NetworksMontavon, Grégoire et al. | 2020
- 5
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Building Nonparametric n-Body Force Fields Using Gaussian Process RegressionGlielmo, Aldo / Zeni, Claudio / Fekete, Ádám / De Vita, Alessandro et al. | 2020
- 6
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Machine-Learning of Atomic-Scale Properties Based on Physical PrinciplesCsányi, Gábor / Willatt, Michael J. / Ceriotti, Michele et al. | 2020
- 7
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Accurate Molecular Dynamics Enabled by Efficient Physically Constrained Machine Learning ApproachesChmiela, Stefan / Sauceda, Huziel E. / Tkatchenko, Alexandre / Müller, Klaus-Robert et al. | 2020
- 8
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Quantum Machine Learning with Response Operators in Chemical Compound SpaceFaber, Felix Andreas / Christensen, Anders S. / Lilienfeld, O. Anatole von et al. | 2020
- 9
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Physical Extrapolation of Quantum Observables by Generalization with Gaussian ProcessesVargas-Hernández, R. A. / Krems, R. V. et al. | 2020
- 10
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Message Passing Neural NetworksGilmer, Justin / Schoenholz, Samuel S. / Riley, Patrick F. / Vinyals, Oriol / Dahl, George E. et al. | 2020
- 11
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Learning Representations of Molecules and Materials with Atomistic Neural NetworksSchütt, Kristof T. / Tkatchenko, Alexandre / Müller, Klaus-Robert et al. | 2020
- 12
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Molecular Dynamics with Neural Network PotentialsGastegger, Michael / Marquetand, Philipp et al. | 2020
- 13
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High-Dimensional Neural Network Potentials for Atomistic SimulationsHellström, Matti / Behler, Jörg et al. | 2020
- 14
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Construction of Machine Learned Force Fields with Quantum Chemical Accuracy: Applications and Chemical InsightsSauceda, Huziel E. / Chmiela, Stefan / Poltavsky, Igor / Müller, Klaus-Robert / Tkatchenko, Alexandre et al. | 2020
- 15
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Active Learning and Uncertainty EstimationShapeev, Alexander / Gubaev, Konstantin / Tsymbalov, Evgenii / Podryabinkin, Evgeny et al. | 2020
- 16
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Machine Learning for Molecular Dynamics on Long TimescalesNoé, Frank et al. | 2020
- 17
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Database-Driven High-Throughput Calculations and Machine Learning Models for Materials DesignArmiento, Rickard et al. | 2020
- 18
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Polymer Genome: A Polymer Informatics Platform to Accelerate Polymer DiscoveryChandrasekaran, Anand / Kim, Chiho / Ramprasad, Rampi et al. | 2020
- 19
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Bayesian Optimization in Materials ScienceHou, Zhufeng / Tsuda, Koji et al. | 2020
- 20
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Recommender Systems for Materials DiscoverySeko, Atsuto / Hayashi, Hiroyuki / Kashima, Hisashi / Tanaka, Isao et al. | 2020
- 21
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Generative Models for Automatic Chemical DesignSchwalbe-Koda, Daniel / Gómez-Bombarelli, Rafael et al. | 2020