Image de couverture de livre

Downsizing Machine Learning Models by Optimization through Ising Models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Okamoto, Yasuharu
Format:	Preprint
Publié:	2025
Sujets:	Materials Science
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

$L_0$ Regularization of Field-Aware Factorization Machine through Ising Model
par: Okamoto, Yasuharu
Publié: (2024)

Boltzmann Reinforcement Learning for Noise resilience in Analog Ising Machines
par: Choudhary, Aditya, et autres
Publié: (2026)

Augmentation of the Electron Counting Rule with Ising Model
par: Kawka, Karol, et autres
Publié: (2024)

250 Magnetic Tunnel Junctions-Based Probabilistic Ising Machine
par: Yang, Shuhan, et autres
Publié: (2025)

Electronic Self-Organization in the β-Pyrochlore Oxide CsW2O6
par: Okamoto, Yoshihiko
Publié: (2024)

Accelerating Optimal Elemental Configuration Search in Crystal using Ising Machine
par: Ichikawa, Kazuhide, et autres
Publié: (2023)

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling?
par: Shen, Chen, et autres
Publié: (2026)

CRYSIM: Prediction of Symmetric Structures of Large Crystals with GPU-based Ising Machines
par: Liang, Chen, et autres
Publié: (2025)

Optimizing Cross-Domain Transfer for Universal Machine Learning Interatomic Potentials
par: Kim, Jaesun, et autres
Publié: (2025)

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials
par: Fang, Zhenyao, et autres
Publié: (2025)

Machine Learning Modeling of Temperature-Dependent Optoelectronic Properties of Anharmonic Solid Solutions
par: Benítez, Pol, et autres
Publié: (2026)

Machine Learning Prediction Models for Solid Electrolytes based on Lattice Dynamics Properties
par: Kim, Jiyeon, et autres
Publié: (2024)

Monte Carlo Simulation of Anisotropic Ising Model Using Metropolis and Wolff Algorithm
par: Iqbal, Basit, et autres
Publié: (2024)

Computationally Efficient Machine-Learned Model for GST Phase Change Materials via Direct and Indirect Learning
par: Dunton, Owen R., et autres
Publié: (2024)

Robustness of Local Predictions in Atomistic Machine Learning Models
par: Chong, Sanggyu, et autres
Publié: (2023)

Best of Both Worlds: Enforcing Detailed Balance in Machine Learning Models of Transition Rates
par: Talapatra, Anjana Anu, et autres
Publié: (2024)

Accelerated Prediction of Temperature-Dependent Lattice Thermal Conductivity via Ensembled Machine Learning Models
par: Paliwal, Piyush, et autres
Publié: (2025)

Data-Driven Modeling of Dislocation Mobility from Atomistics using Physics-Informed Machine Learning
par: Tian, Yifeng, et autres
Publié: (2024)

Machine Learning Enables Optimization of Diamond for Quantum Applications
par: deQuilettes, Dane W., et autres
Publié: (2025)

Flexible Cutoff Learning: Optimizing Machine Learning Potentials After Training
par: Oerder, Rick, et autres
Publié: (2026)

Revealing Fast Ionic Conduction in Solid Electrolytes through Machine Learning Accelerated Raman Calculations
par: Grumet, Manuel, et autres
Publié: (2025)

Discovery of Novel Silicon Allotropes with Optimized Band Gaps to Enhance Solar Cell Efficiency through Evolutionary Algorithms and Machine Learning
par: Yaghoobi, Mostafa, et autres
Publié: (2024)

Record Acceleration of the Two-Dimensional Ising Model Using High-Performance Wafer Scale Engine
par: Van Essendelft, Dirk, et autres
Publié: (2024)

Enhancing Machine Learning Potentials through Transfer Learning across Chemical Elements
par: Röcken, Sebastien, et autres
Publié: (2025)

A Methodological Study on Data Representation for Machine Learning Modelling of Thermal Conductivity of Rare-Earth Oxides
par: Chowdhury, Amiya, et autres
Publié: (2025)

Driving Thermoelectric Optimization in AgSbTe2 via Design of Experiments and Machine Learning
par: Pöhls, Jan-Hendrik, et autres
Publié: (2024)

Data-driven Prediction of Ionic Conductivity in Solid-State Electrolytes with Machine Learning and Large Language Models
par: Kim, Haewon, et autres
Publié: (2026)

Equivariant Atomic and Lattice Modeling Using Geometric Deep Learning for Crystal Structure Optimization
par: Yang, Ziduo, et autres
Publié: (2025)

Learning the Electrostatic Response of the Electron Density through a Symmetry-Adapted Vector Field Model
par: Rossi, Mariana, et autres
Publié: (2025)

Automated Machine Learning Pipeline: Large Language Models-Assisted Automated Dataset Generation for Training Machine-Learned Interatomic Potentials
par: Lahouari, Adam, et autres
Publié: (2025)

Scalable Machine Learning Model for Energy Decomposition Analysis in Aqueous Systems
par: Tahmasbi, Hossein, et autres
Publié: (2025)

Cobalt-Based Pyroxenes: A New Playground for Kitaev Physics and Ising Model Realization
par: Maksimov, Pavel A., et autres
Publié: (2024)

Combining Machine Learning Models with First-Principles High-Throughput Calculation to Accelerate the Search of Promising Thermoelectric Materials
par: Fan, Tao, et autres
Publié: (2024)

Enhancing Magnetocaloric Material Discovery: A Machine Learning Approach Using an Autogenerated Database by Large Language Models
par: Yuan, Jiaoyue, et autres
Publié: (2024)

Voltage Mining for (De)lithiation-stabilized Cathodes and a Machine Learning Model for Li-ion Cathode Voltage
par: Li, Haoming Howard, et autres
Publié: (2024)

A Self-Evolving Machine-Learning-Based Kinetic Monte Carlo Method for Modelling Thin-Film Growth
par: Kimari, Jyri, et autres
Publié: (2026)

Integrating Machine Learning with Triboelectric Nanogenerators: Optimizing Electrode Materials and Doping Strategies for Intelligent Energy Harves
par: Xu, Guanping, et autres
Publié: (2025)

Understanding Magnesium Dissolution through Machine Learn-ing Molecular Dynamics
par: Liu, Zhoulin, et autres
Publié: (2025)

Electric-Field Driven Nuclear Dynamics of Liquids and Solids from a Multi-Valued Machine-Learned Dipolar Model
par: Stocco, Elia, et autres
Publié: (2025)

Composite Material Design for Optimized Fracture Toughness Using Machine Learning
par: Jahromi, Mohammad Naqizadeh, et autres
Publié: (2024)