Cover Image

Inelastic Constitutive Kolmogorov-Arnold Networks: A generalized framework for automated discovery of interpretable inelastic material models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ji, Chenyi, Abdolazizi, Kian P., Holthusen, Hagen, Cyron, Christian J., Linka, Kevin
Format:	Preprint
Published:	2026
Subjects:	Materials Science Artificial Intelligence Computational Physics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Constitutive Kolmogorov-Arnold Networks (CKANs): Combining Accuracy and Interpretability in Data-Driven Material Modeling
by: Abdolazizi, Kian P., et al.
Published: (2025)

A generalized dual potential for inelastic Constitutive Artificial Neural Networks: A JAX implementation at finite strains
by: Holthusen, Hagen, et al.
Published: (2025)

Automating modeling in mechanics: LLMs as designers of physics-constrained neural networks for constitutive modeling of materials
by: Tacke, Marius, et al.
Published: (2025)

Automated Model Discovery for Tensional Homeostasis: Constitutive Machine Learning in Growth and Remodeling
by: Holthusen, Hagen, et al.
Published: (2024)

Theory and implementation of inelastic Constitutive Artificial Neural Networks
by: Holthusen, Hagen, et al.
Published: (2023)

LLM-driven design of physics-constrained constitutive models: two agents are better than one
by: Tacke, Marius, et al.
Published: (2026)

Accounting for plasticity: An extension of inelastic Constitutive Artificial Neural Networks
by: Boes, Birte, et al.
Published: (2024)

Watching Physics: the Generative Science of Matter and Motion
by: Holthusen, Hagen, et al.
Published: (2026)

A Complement to Neural Networks for Anisotropic Inelasticity at Finite Strains
by: Holthusen, Hagen, et al.
Published: (2025)

Autoencoder-based non-intrusive model order reduction in continuum mechanics
by: Kehls, Jannick, et al.
Published: (2025)

On sparse regression, Lp-regularization, and automated model discovery
by: McCulloch, Jeremy A., et al.
Published: (2023)

On sparse regression, Lp‐regularization, and automated model discovery
by: Jeremy A. McCulloch, et al.
Published: (2024)

Non-smooth optimization meets automated material model discovery
by: Flaschel, Moritz, et al.
Published: (2025)

Kolmogorov-Arnold Networks in Thermoelectric Materials Design
by: Fronzi, Marco, et al.
Published: (2025)

A Comprehensive Framework for Predictive Computational Modeling of Growth and Remodeling in Tissue-Engineered Cardiovascular Implants
by: Sesa, Mahmoud, et al.
Published: (2025)

Kolmogorov-Arnold Networks Applied to Materials Property Prediction
by: Jacobs, Ryan, et al.
Published: (2026)

Kolmogorov--Arnold networks in molecular dynamics
by: Nagai, Yuki, et al.
Published: (2024)

A tomographic interpretation of structure-property relations for materials discovery
by: Ortega-Ochoa, Raul, et al.
Published: (2025)

Kolmogorov-Arnold Neural Networks for High-Entropy Alloys Design
by: Bandyopadhyay, Yagnik, et al.
Published: (2024)

Interpretation of Crystal Energy Landscapes with Kolmogorov-Arnold Networks
by: Zu, Gen, et al.
Published: (2026)

A closed-loop AI framework for hypothesis-driven and interpretable materials design
by: Ji, Kangyu, et al.
Published: (2025)

A hierarchy of thermodynamics learning frameworks for inelastic constitutive modeling
by: Jones, Reese E., et al.
Published: (2026)

Polyconvex inelastic constitutive artificial neural networks
by: Hagen Holthusen, et al.
Published: (2024)

Data-driven model discovery with Kolmogorov-Arnold networks
by: Moradi, Mohammadamin, et al.
Published: (2024)

Efficient prediction of potential energy surface and physical properties with Kolmogorov-Arnold Networks
by: Wang, Rui, et al.
Published: (2024)

Active partitioning: inverting the paradigm of active learning
by: Tacke, Marius, et al.
Published: (2024)

Scattering-Based Structural Inversion of Soft Materials via Kolmogorov-Arnold Networks
by: Tung, Chi-Huan, et al.
Published: (2024)

Spectra-Scope : A toolkit for automated and interpretable characterization of material properties from spectral data
by: Johnson, Amalya C., et al.
Published: (2026)

An attention-based neural ordinary differential equation framework for modeling inelastic processes
by: Jones, Reese E., et al.
Published: (2025)

A Calibration Approach for Elasticity Estimation with Medical Tools
by: Grube, Sarah, et al.
Published: (2024)

Are diffusion models ready for materials discovery in unexplored chemical space?
by: Kim, Sanghyun, et al.
Published: (2025)

EPi-cKANs: Elasto-Plasticity Informed Kolmogorov-Arnold Networks Using Chebyshev Polynomials
by: Mostajeran, Farinaz, et al.
Published: (2024)

Adaptive Material Fingerprinting for the fast discovery of polyconvex feature combinations in isotropic and anisotropic hyperelasticity
by: Flaschel, Moritz, et al.
Published: (2026)

A topology optimisation framework to design test specimens for one-shot identification or discovery of material models
by: Ghouli, Saeid, et al.
Published: (2025)

Screening 39 billion protostructures for materials discovery
by: Parackal, Abhijith S, et al.
Published: (2026)

Incorporating quasiparticle and excitonic properties into material discovery
by: Biswas, Tathagata, et al.
Published: (2024)

Best-in-class modeling: A novel strategy to discover constitutive models for soft matter systems
by: Linka, Kevin, et al.
Published: (2024)

Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
by: Evans, Matthew L., et al.
Published: (2024)

Forecasting VIX using interpretable Kolmogorov-Arnold networks
by: Cho, So-Yoon, et al.
Published: (2025)

Navigating energy landscapes for materials discovery: Integrating modeling, simulation, and machine learning
by: Sajid Mannan, et al.
Published: (2024)