Image de couverture de livre

HyperCAN: Hypernetwork-Driven Deep Parameterized Constitutive Models for Metamaterials

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zheng, Li, Kochmann, Dennis M., Kumar, Siddhant
Format:	Preprint
Publié:	2024
Sujets:	Computational Engineering, Finance, and Science
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Algebraic Language Models for Inverse Design of Metamaterials via Diffusion Transformers
par: Zheng, Li, et autres
Publié: (2025)

Unifying the design space and optimizing linear and nonlinear truss metamaterials by generative modeling
par: Zheng, Li, et autres
Publié: (2023)

Inverse-design of nonlinear mechanical metamaterials via video denoising diffusion models
par: Bastek, Jan-Hendrik, et autres
Publié: (2023)

A mixed-order quasicontinuum approach for beam-based architected materials with application to fracture
par: Kraschewski, Kevin, et autres
Publié: (2024)

Physics-Informed Neural Networks for Shell Structures
par: Bastek, Jan-Hendrik, et autres
Publié: (2022)

Physics-Informed Diffusion Models
par: Bastek, Jan-Hendrik, et autres
Publié: (2024)

Deep learning reveals key predictors of thermal conductivity in covalent organic frameworks
par: Thakolkaran, Prakash, et autres
Publié: (2024)

Inverse designing surface curvatures by deep learning
par: Guo, Yaqi, et autres
Publié: (2023)

Mixing Data-Driven and Physics-Based Constitutive Models using Uncertainty-Driven Phase Fields
par: Storm, J., et autres
Publié: (2025)

Enhanced Floating Isogeometric Analysis
par: Hille, Helge C., et autres
Publié: (2023)

Hetero-EUCLID: Interpretable model discovery for heterogeneous hyperelastic materials using stress-unsupervised learning
par: Chaurasiya, Kanhaiya Lal, et autres
Publié: (2025)

Deep Neural Operator Enabled Concurrent Multitask Design for Multifunctional Metamaterials under Heterogeneous Fields
par: Lee, Doksoo, et autres
Publié: (2023)

Geom-DeepONet: A Point-cloud-based Deep Operator Network for Field Predictions on 3D Parameterized Geometries
par: He, Junyan, et autres
Publié: (2024)

Experiment-informed finite-strain inverse design of spinodal metamaterials
par: Thakolkaran, Prakash, et autres
Publié: (2023)

Constitutive Manifold Neural Networks
par: Schuttert, Wouter J., et autres
Publié: (2025)

COMMET: orders-of-magnitude speed-up in finite element method via batch-vectorized neural constitutive updates
par: Alheit, Benjamin, et autres
Publié: (2025)

Stress-constrained Topology Optimization for Metamaterial Microstructure Design
par: Chen, Yanda, et autres
Publié: (2026)

Data-Driven, Parameterized Reduced-order Models for Predicting Distortion in Metal 3D Printing
par: Deo, Indu Kant, et autres
Publié: (2024)

A discontinuous Galerkin / cohesive zone model approach for the computational modeling of fracture in geometrically exact slender beams
par: Kota, Sai Kubair, et autres
Publié: (2023)

Landscape-Aware Bandit Hyper-Heuristics for Online Operator Selection in UAV Inspection Routing
par: Wei, Junhao, et autres
Publié: (2026)

Enhancing Multiscale Simulations with Constitutive Relations-Aware Deep Operator Networks
par: Eivazi, Hamidreza, et autres
Publié: (2024)

CardioFit: A WebGL-Based Tool for Fast and Efficient Parameterization of Cardiac Action Potential Models to Fit User-Provided Data
par: Cairns, Darby I., et autres
Publié: (2025)

Hyperfastrl: Hypernetwork-based reinforcement learning for unified control of parametric chaotic PDEs
par: Sapkota, Anil, et autres
Publié: (2026)

Learning ultra-compressible hyperelasticity with splines: Constitutive asymmetries and non-unique representations
par: Moreno-Mateos, Miguel Angel, et autres
Publié: (2026)

GUST: Quantifying Free-Form Geometric Uncertainty of Metamaterials Using Small Data
par: Zheng, Jiahui, et autres
Publié: (2025)

XNet-Enhanced Deep BSDE Method and Numerical Analysis
par: Zheng, Xiaotao, et autres
Publié: (2025)

Advancements in Constitutive Model Calibration: Leveraging the Power of Full-Field DIC Measurements and In-Situ Load Path Selection for Reliable Parameter Inference
par: Ricciardi, Denielle, et autres
Publié: (2024)

Collatz-Weyl Generators: High Quality and High Throughput Parameterized Pseudorandom Number Generators
par: Działa, Tomasz R.
Publié: (2023)

Parameterized crack modelling based on a localized non-intrusive reduced basis method
par: Chasapi, Margarita
Publié: (2025)

Unsupervised Constitutive Model Discovery from Sparse and Noisy Data
par: Narouie, Vahab Knauf, et autres
Publié: (2025)

Scalable Active Metamaterials for Shape-Morphing
par: Cui, Jipeng, et autres
Publié: (2026)

Stochastic Deep Learning Surrogate Models for Uncertainty Propagation in Microstructure-Properties of Ceramic Aerogels
par: Islam, Md Azharul, et autres
Publié: (2025)

SeisGPT: A Physics-Informed Data-Driven Large Model for Real-Time Seismic Response Prediction
par: Meng, Shiqiao, et autres
Publié: (2024)

Hyper-reduction-free reduced-order Newton solvers for projection-based model-order reduction of nonlinear dynamical systems
par: Magargal, Liam K., et autres
Publié: (2026)

Toward a Robust and Generalizable Metamaterial Foundation Model
par: Kim, Namjung, et autres
Publié: (2025)

Bridging the Gap Between Data-Driven And Theory-Driven Modelling - Leveraging Causal Machine Learning for Integrative Modelling of Dynamical Systems
par: Gonzalez, David Zapata, et autres
Publié: (2024)

Deep Feynman-Kac Methods for High-dimensional Semilinear Parabolic Equations: Revisit
par: Zheng, Xiaotao, et autres
Publié: (2025)

Identifying and Quantifying Financial Bubbles with the Hyped Log-Periodic Power Law Model
par: Cao, Zheng, et autres
Publié: (2025)

Local learning for stable backpropagation-free neural network training towards physical learning
par: Guo, Yaqi, et autres
Publié: (2026)

Learning Parameterized Nonlinear Elasticity on Curved Surfaces
par: Liu, Yankang, et autres
Publié: (2026)