Unsupervised machine learning for detection of phase transitions in off-lattice systems. II. Applications

Hierarchical modeling of molecular energies using a deep neural network

(2018) Nicholas Lubbers et al.   JOURNAL OF CHEMICAL PHYSICS

SchNet – A deep learning architecture for molecules and materials

(2018) K. T. Schütt et al.   JOURNAL OF CHEMICAL PHYSICS

Machine learning of frustrated classical spin models (II): Kernel principal component analysis

(2018) Ce Wang et al.   Frontiers of Physics

Unsupervised machine learning for detection of phase transitions in off-lattice systems. I. Foundations

(2018) R. B. Jadrich et al.   JOURNAL OF CHEMICAL PHYSICS

Learning phase transitions by confusion

(2017) Evert P. L. van Nieuwenburg et al.   Nature Physics

Machine learning phases of matter

(2017) Juan Carrasquilla et al.   Nature Physics

Enhanced hyperuniformity from random reorganization

(2017) Daniel Hexner et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Scalable Metropolis Monte Carlo for simulation of hard shapes

(2016) Joshua A. Anderson et al.   COMPUTER PHYSICS COMMUNICATIONS

An introduction to the statistical physics of active matter: motility-induced phase separation and the “generic instability” of active gels

(2016) Davide Marenduzzo   European Physical Journal-Special Topics

On the formation of equilibrium gels via a macroscopic bond limitation

(2016) B. A. Lindquist et al.   JOURNAL OF CHEMICAL PHYSICS

Criticality and correlated dynamics at the irreversibility transition in periodically driven colloidal suspensions

(2016) Elsen Tjhung et al.   JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT

Active Particles in Complex and Crowded Environments

(2016) Clemens Bechinger et al.   REVIEWS OF MODERN PHYSICS

Strong scaling of general-purpose molecular dynamics simulations on GPUs

(2015) Jens Glaser et al.   COMPUTER PHYSICS COMMUNICATIONS

Contact- and distance-based principal component analysis of protein dynamics

(2015) Matthias Ernst et al.   JOURNAL OF CHEMICAL PHYSICS

Learning scheme to predict atomic forces and accelerate materials simulations

(2015) V. Botu et al.   PHYSICAL REVIEW B

Nonequilibrium structure of colloidal dumbbells under oscillatory shear

(2015) Nils Heptner et al.   PHYSICAL REVIEW E

Adaptive machine learning framework to accelerateab initiomolecular dynamics

(2014) Venkatesh Botu et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Phase diagram of two-dimensional hard ellipses

(2014) Gustavo Bautista-Carbajal et al.   JOURNAL OF CHEMICAL PHYSICS

Hard ellipses: Equation of state, structure, and self-diffusion

(2013) Wen-Sheng Xu et al.   JOURNAL OF CHEMICAL PHYSICS

Connecting the random organization transition and jamming within a unifying model system

(2013) Lars Milz et al.   PHYSICAL REVIEW E

Driving self-assembly and emergent dynamics in colloidal suspensions by time-dependent magnetic fields

(2013) James E Martin et al.   REPORTS ON PROGRESS IN PHYSICS

Oscillatory shear-induced 3D crystalline order in colloidal hard-sphere fluids

(2012) T. H. Besseling et al.   Soft Matter

General purpose molecular dynamics simulations fully implemented on graphics processing units

(2008) Joshua A. Anderson et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Random organization in periodically driven systems

(2008) Laurent Corté et al.   Nature Physics