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High-entropy nanoparticles: Synthesis-structure-property relationships and data-driven discovery

Science (American Association for the Advancement of Science), 2022-04, Vol.376 (6589), p.eabn3103-eabn3103

2022

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Equation-free multiscale computation: algorithms and applications

Annual review of physical chemistry, 2009-01, Vol.60 (1), p.321-344

2009

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A classification scheme for chimera states

Chaos (Woodbury, N.Y.), 2016-09, Vol.26 (9)

2016

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A kernel-based method for data-driven koopman spectral analysis

Journal of computational dynamics, 2015, Vol.2 (2), p.247-265

2015

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Learning emergent partial differential equations in a learned emergent space

Nature communications, 2022-06, Vol.13 (1), p.3318-3318, Article 3318

2022

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Machine learning-assisted crystal engineering of a zeolite

Nature communications, 2023-05, Vol.14 (1), p.3152-3152, Article 3152

2023

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Detecting intrinsic slow variables in stochastic dynamical systems by anisotropic diffusion maps

Proceedings of the National Academy of Sciences - PNAS, 2009-09, Vol.106 (38), p.16090-16095

2009

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Systematic determination of order parameters for chain dynamics using diffusion maps

Proceedings of the National Academy of Sciences - PNAS, 2010-08, Vol.107 (31), p.13597-13602

2010

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Task-oriented machine learning surrogates for tipping points of agent-based models

Nature communications, 2024-05, Vol.15 (1), p.4117-4117, Article 4117

2024

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Systematic characterization of protein folding pathways using diffusion maps: application to Trp-cage miniprotein

The Journal of chemical physics, 2015-02, Vol.142 (8), p.085101-085101

2015

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Inherent noise can facilitate coherence in collective swarm motion

Proceedings of the National Academy of Sciences - PNAS, 2009-04, Vol.106 (14), p.5464-5469

2009

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Limits of entrainment of circadian neuronal networks

Chaos (Woodbury, N.Y.), 2023-01, Vol.33 (1), p.013137

2023

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On learning Hamiltonian systems from data

Chaos (Woodbury, N.Y.), 2019-12, Vol.29 (12)

2019

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Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator

Chaos (Woodbury, N.Y.), 2017-10, Vol.27 (10)

2017

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Dissipative particle dynamics simulations of polymer-protected nanoparticle self-assembly

The Journal of chemical physics, 2011-11, Vol.135 (18), p.184903-184903-10

2011

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Coarse-grained analysis of stochasticity-induced switching between collective motion states

Proceedings of the National Academy of Sciences - PNAS, 2007-04, Vol.104 (14), p.5931-5935

2007

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Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

The Journal of chemical physics, 2014-09, Vol.141 (11), p.114102-114102

2014

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Optical imaging and control of genetically designated neurons in functioning circuits

Annual review of neuroscience, 2005-01, Vol.28 (1), p.533-563

2005

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Transformations establishing equivalence across neural networks: When have two networks learned the same task?

Chaos (Woodbury, N.Y.), 2024-07, Vol.34 (7)

2024

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Reconstruction of normal forms by learning informed observation geometries from data

Proceedings of the National Academy of Sciences - PNAS, 2017-09, Vol.114 (38), p.E7865-E7874

2017

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Active learning of ternary alloy structures and energies

npj computational materials, 2024-05, Vol.10 (1), p.116-11, Article 116

2024

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Programmable heating and quenching for efficient thermochemical synthesis

Nature (London), 2022-05, Vol.605 (7910), p.470-476

2022

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Bacterial population solitary waves can defeat rings of funnels

New journal of physics, 2017-03, Vol.19 (3), p.35002

2017

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Coarse-scale PDEs from fine-scale observations via machine learning

Chaos (Woodbury, N.Y.), 2020-01, Vol.30 (1)

2020

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Depolymerization of plastics by means of electrified spatiotemporal heating

Nature (London), 2023-04, Vol.616 (7957), p.488-494

2023

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High-entropy nanoparticles: Synthesis-structure-property relationships and data-driven discovery

Equation-free multiscale computation: algorithms and applications

A classification scheme for chimera states

A kernel-based method for data-driven koopman spectral analysis

Learning emergent partial differential equations in a learned emergent space

Machine learning-assisted crystal engineering of a zeolite

Detecting intrinsic slow variables in stochastic dynamical systems by anisotropic diffusion maps

Systematic determination of order parameters for chain dynamics using diffusion maps

Task-oriented machine learning surrogates for tipping points of agent-based models

Systematic characterization of protein folding pathways using diffusion maps: application to Trp-cage miniprotein

Inherent noise can facilitate coherence in collective swarm motion

Limits of entrainment of circadian neuronal networks

On learning Hamiltonian systems from data

Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator

Dissipative particle dynamics simulations of polymer-protected nanoparticle self-assembly

Coarse-grained analysis of stochasticity-induced switching between collective motion states

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

Optical imaging and control of genetically designated neurons in functioning circuits

Transformations establishing equivalence across neural networks: When have two networks learned the same task?

Reconstruction of normal forms by learning informed observation geometries from data

Active learning of ternary alloy structures and energies

Programmable heating and quenching for efficient thermochemical synthesis

Bacterial population solitary waves can defeat rings of funnels

Coarse-scale PDEs from fine-scale observations via machine learning

Depolymerization of plastics by means of electrified spatiotemporal heating

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