Gia-Wei Chern

CoRR, April, 2026

Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems.

[BibT_eX]

[DOI]

CoRR, April, 2026

Graph neural network force fields for adiabatic dynamics of lattice Hamiltonians.

[BibT_eX]

[DOI]

CoRR, March, 2026

Machine-learning force-field models for dynamical simulations of metallic magnets.

[BibT_eX]

[DOI]

CoRR, February, 2026

Transformer Learning of Chaotic Collective Dynamics in Many-Body Systems.

[BibT_eX]

[DOI]

Ho Jang

CoRR, January, 2026

Machine learning nonequilibrium phase transitions in charge-density wave insulators.

[BibT_eX]

[DOI]

CoRR, January, 2026

Equivariant Neural Networks for Force-Field Models of Lattice Systems.

[BibT_eX]

[DOI]

CoRR, January, 2026

2025

Learning Degenerate Manifolds of Frustrated Magnets with Boltzmann Machines.

[BibT_eX]

[DOI]

Jackson C. Glass

CoRR, November, 2025

Geometric Analysis of Magnetic Labyrinthine Stripe Evolution via U-Net Segmentation.

[BibT_eX]

[DOI]

CoRR, September, 2025

Machine Learning Force-Field Approach for Itinerant Electron Magnets.

[BibT_eX]

[DOI]

CoRR, January, 2025

2024

Enhanced coarsening of charge density waves induced by electron correlation: Machine-learning enabled large-scale dynamical simulations.

[BibT_eX]

[DOI]

CoRR, 2024

Echo State network for coarsening dynamics of charge density waves.

[BibT_eX]

[DOI]

Clement Dinh

CoRR, 2024

Machine learning force-field model for kinetic Monte Carlo simulations of itinerant Ising magnets.

[BibT_eX]

[DOI]

Alexa Tyberg

CoRR, 2024

Machine learning approach for vibronically renormalized electronic band structures.

[BibT_eX]

[DOI]

CoRR, 2024

Kinetics of orbital ordering in cooperative Jahn-Teller models: Machine-learning enabled large-scale simulations.

[BibT_eX]

[DOI]

CoRR, 2024

Coarsening of chiral domains in itinerant electron magnets: A machine learning force field approach.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Machine learning force-field models for metallic spin glass.

[BibT_eX]

[DOI]

Menglin Shi

CoRR, 2023

Machine learning for structure-property relationships: Scalability and limitations.

[BibT_eX]

[DOI]

Zhongzheng Tian

CoRR, 2023

Machine learning for phase ordering dynamics of charge density waves.

[BibT_eX]

[DOI]

Chen Cheng

CoRR, 2023

2022

Machine learning predictions for local electronic properties of disordered correlated electron systems.

[BibT_eX]

[DOI]

CoRR, 2022

Descriptors for Machine Learning Model of Generalized Force Field in Condensed Matter Systems.

[BibT_eX]

[DOI]

CoRR, 2022

2021

Machine learning nonequilibrium electron forces for adiabatic spin dynamics.

[BibT_eX]

[DOI]

CoRR, 2021

Anomalous phase separation and hidden coarsening of super-clusters in the Falicov-Kimball model.

[BibT_eX]

[DOI]

CoRR, 2021

Arrested phase separation in double-exchange models: machine-learning enabled large-scale simulation.

[BibT_eX]

[DOI]

CoRR, 2021

2020

Machine learning dynamics of phase separation in correlated electron magnets.

[BibT_eX]

[DOI]

Preetha Saha

CoRR, 2020

2019

Artificial Spin Ice Phase-Change Memory Resistors.

[BibT_eX]

[DOI]

Francesco Caravelli