Imagen de Portada

Multimodal Machine Learning for Integrating Heterogeneous Analytical Systems

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Muroga, Shun, Nakajima, Hideaki, Shimizu, Taiyo, Kobashi, Kazufumi, Hata, Kenji
Formato:	Preprint
Publicado:	2026
Materias:	Materials Science Soft Condensed Matter Artificial Intelligence Machine Learning Data Analysis, Statistics and Probability
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Explainable Multimodal Machine Learning for Revealing Structure-Property Relationships in Carbon Nanotube Fibers
por: Kimura, Daisuke, et al.
Publicado: (2025)

Inferring interaction potentials from stochastic particle trajectories
por: King, Ella M., et al.
Publicado: (2024)

Comparing unsupervised learning methods for local structural identification in colloidal systems
por: Ulugöl, Alptuğ, et al.
Publicado: (2025)

Structural Decomposition of UV--Visible Spectral Variation: Azobenzene in Ethanol Solution
por: Eronen, Eemeli A., et al.
Publicado: (2025)

Global $q$-dependent inverse transforms of intensity autocorrelation data
por: Eklund, Tobias, et al.
Publicado: (2025)

On the analysis of two-time correlation functions: equilibrium vs non-equilibrium systems
por: Ragulskaya, Anastasia, et al.
Publicado: (2024)

On how to determine surface roughness power spectra
por: Rodriguez, N., et al.
Publicado: (2024)

Inference of a time delay in stochastic systems
por: Kopp, Robin A., et al.
Publicado: (2025)

Physical Embodiment Enables Information Processing Beyond Explicit Sensing in Active Matter
por: Paul, Diptabrata, et al.
Publicado: (2025)

Theoretical correction methods for optical tweezers: Acquisition of potentials of mean forces between colloidal particles in a bulk and on a surface
por: Amano, Ken-ichi, et al.
Publicado: (2020)

Model-free estimation in scattering analysis of microscopy
por: Lin, Tong, et al.
Publicado: (2026)

Calibrating a Finite-strain Phase-field Model of Fracture for Bonded Granular Materials with Uncertainty Quantification
por: Schmid, Abigail C., et al.
Publicado: (2025)

Beyond Local Structures In Critical Supercooled Water Through Unsupervised Learning
por: Donkor, Edward Danquah, et al.
Publicado: (2024)

Machine Learning Analysis of Anomalous Diffusion
por: Cai, Wenjie, et al.
Publicado: (2024)

Machine learning based prediction of dynamical clustering in granular gases
por: Sata, Sai Preetham, et al.
Publicado: (2025)

Learning dynamical models from stochastic trajectories
por: Ronceray, Pierre
Publicado: (2024)

Criticality in an imidazolium ionic liquid fully wetting a sapphire support
por: Höllring, Kevin, et al.
Publicado: (2024)

Brownian friction dynamics: fluctuations in sliding distance
por: Xu, Ruibin, et al.
Publicado: (2024)

Constrained composite Bayesian optimization for rational synthesis of polymeric particles
por: Wang, Fanjin, et al.
Publicado: (2024)

Error evaluation of partial scattering functions obtained from contrast variation small-angle neutron scattering
por: Mayumi, Koichi, et al.
Publicado: (2024)

Light-scattering reconstruction of transparent shapes using neural networks
por: Miara, Tymoteusz, et al.
Publicado: (2023)

Anomalous Dynamics of Superparamagnetic Colloidal Microrobots with Tailored Statistics
por: Gentili, Alessia, et al.
Publicado: (2024)

Principled model selection for stochastic dynamics
por: Gerardos, Andonis, et al.
Publicado: (2025)

The Hitchhiker's Guide to Differential Dynamic Microscopy
por: Lattuada, Enrico, et al.
Publicado: (2025)

A fast transferable method for predicting the glass transition temperature of polymers from chemical structure
por: Brierley-Croft, Sebastian, et al.
Publicado: (2024)

Data-Efficient Learning of Anomalous Diffusion with Wavelet Representations: Enabling Direct Learning from Experimental Trajectories
por: Wang, Gongyi, et al.
Publicado: (2025)

Flat-histogram algorithms: optimal parameters and extended application
por: Shakirov, Timur
Publicado: (2024)

Machine Learning Based Identification of Solvents from Post-Desiccation Patterns
por: Morán-Cortés, Jesús Israel, et al.
Publicado: (2026)

Accurate estimation of the normalized mutual information of multidimensional data
por: Nagel, Daniel, et al.
Publicado: (2024)

Quantitative evaluation of methods to analyze motion changes in single-particle experiments
por: Muñoz-Gil, Gorka, et al.
Publicado: (2023)

Recovering Hidden Degrees of Freedom Using Gaussian Processes
por: Diez, Georg, et al.
Publicado: (2025)

Markov-type state models to describe non-Markovian dynamics
por: Sartore, Sofia, et al.
Publicado: (2024)

Objective comparison of methods to decode anomalous diffusion
por: Muñoz-Gil, Gorka, et al.
Publicado: (2021)

Ab initio uncertainty quantification in scattering analysis of microscopy
por: Gu, Mengyang, et al.
Publicado: (2023)

Information decomposition in complex systems via machine learning
por: Murphy, Kieran A., et al.
Publicado: (2023)

Lost in Projection? Gaussian Filtering Recovers Hidden Conformational States
por: Sartore, Sofia, et al.
Publicado: (2026)

Polymer Knots in Thin Films: Thickness Dependence, Local Effects, and Stiffness
por: Schmitt, Maurice P., et al.
Publicado: (2026)

On the growing length scale in a replica-coupled glassforming liquid
por: Küchler, Niklas, et al.
Publicado: (2024)

Learning minimal representations of stochastic processes with variational autoencoders
por: Fernández-Fernández, Gabriel, et al.
Publicado: (2023)

Directed Polymer Transfer Matrices as a Unified Generator of Distinct One-Point Fluctuation Laws
por: Mu, Sen, et al.
Publicado: (2026)