Shape-informed surrogate models based on signed distance function domain encoding
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | Zhang, Linying, Pagani, Stefano, Zhang, Jun, Regazzoni, Francesco |
|---|---|
| Format: | Preprint |
| Publié: |
2024
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
Shape-informed cardiac mechanics surrogates in data-scarce regimes via geometric encoding and generative augmentation
par: Carrara, Davide, et autres
Publié: (2026)
par: Carrara, Davide, et autres
Publié: (2026)
A model learning framework for inferring the dynamics of transmission rate depending on exogenous variables for epidemic forecasts
par: Ziarelli, Giovanni, et autres
Publié: (2024)
par: Ziarelli, Giovanni, et autres
Publié: (2024)
Learning geometry-dependent lead-field operators for forward ECG modeling
par: Dokuchaev, Arsenii, et autres
Publié: (2026)
par: Dokuchaev, Arsenii, et autres
Publié: (2026)
The internal law of a material can be discovered from its boundary
par: Regazzoni, Francesco
Publié: (2026)
par: Regazzoni, Francesco
Publié: (2026)
Physics-informed neural network estimation of active material properties in time-dependent cardiac biomechanical models
par: Höfler, Matthias, et autres
Publié: (2025)
par: Höfler, Matthias, et autres
Publié: (2025)
Influence of cellular mechano-calcium feedback in numerical models of cardiac electromechanics
par: Radišić, Irena, et autres
Publié: (2025)
par: Radišić, Irena, et autres
Publié: (2025)
Physics-informed Neural Network Estimation of Material Properties in Soft Tissue Nonlinear Biomechanical Models
par: Caforio, Federica, et autres
Publié: (2023)
par: Caforio, Federica, et autres
Publié: (2023)
Physics-constrained identification of graph-based thermal networks for spacecraft digital twins
par: Sosta, Luca, et autres
Publié: (2026)
par: Sosta, Luca, et autres
Publié: (2026)
Symmetry group based domain decomposition to enhance physics-informed neural networks for solving partial differential equations
par: Liu, Ye, et autres
Publié: (2024)
par: Liu, Ye, et autres
Publié: (2024)
Deep adaptive sampling for surrogate modeling without labeled data
par: Wang, Xili, et autres
Publié: (2024)
par: Wang, Xili, et autres
Publié: (2024)
A novel data generation scheme for surrogate modelling with deep operator networks
par: Choubey, Shivam, et autres
Publié: (2024)
par: Choubey, Shivam, et autres
Publié: (2024)
Nonuniform random feature models using derivative information
par: Pieper, Konstantin, et autres
Publié: (2024)
par: Pieper, Konstantin, et autres
Publié: (2024)
Variational Bayesian surrogate modelling with application to robust design optimisation
par: Archbold, Thomas A., et autres
Publié: (2024)
par: Archbold, Thomas A., et autres
Publié: (2024)
Data-Augmented Predictive Deep Neural Network: Enhancing the extrapolation capabilities of non-intrusive surrogate models
par: Sun, Shuwen, et autres
Publié: (2024)
par: Sun, Shuwen, et autres
Publié: (2024)
Multi-fidelity surrogate with heterogeneous input spaces for modeling melt pools in laser-directed energy deposition
par: Menon, Nandana, et autres
Publié: (2024)
par: Menon, Nandana, et autres
Publié: (2024)
Neural and spectral operator surrogates: unified construction and expression rate bounds
par: Herrmann, Lukas, et autres
Publié: (2022)
par: Herrmann, Lukas, et autres
Publié: (2022)
LDDMM stochastic interpolants: an application to domain uncertainty quantification in hemodynamics
par: Katz, Sarah, et autres
Publié: (2026)
par: Katz, Sarah, et autres
Publié: (2026)
Structure and asymptotic preserving deep neural surrogates for uncertainty quantification in multiscale kinetic equations
par: Chen, Wei, et autres
Publié: (2025)
par: Chen, Wei, et autres
Publié: (2025)
Bi-fidelity Variational Auto-encoder for Uncertainty Quantification
par: Cheng, Nuojin, et autres
Publié: (2023)
par: Cheng, Nuojin, et autres
Publié: (2023)
PTPI-DL-ROMs: pre-trained physics-informed deep learning-based reduced order models for nonlinear parametrized PDEs
par: Brivio, Simone, et autres
Publié: (2024)
par: Brivio, Simone, et autres
Publié: (2024)
Physics-informed reduced order model with conditional neural fields
par: Kim, Minji, et autres
Publié: (2024)
par: Kim, Minji, et autres
Publié: (2024)
A deformation-based framework for learning solution mappings of PDEs defined on varying domains
par: Xiao, Shanshan, et autres
Publié: (2024)
par: Xiao, Shanshan, et autres
Publié: (2024)
Data efficient surrogate modeling for engineering design: Ensemble-free batch mode deep active learning for regression
par: Kapoor, Sarthak, et autres
Publié: (2022)
par: Kapoor, Sarthak, et autres
Publié: (2022)
Random test functions, $H^{-1}$ norm equivalence, and stochastic variational physics-informed neural networks
par: Marcondes, Diego
Publié: (2026)
par: Marcondes, Diego
Publié: (2026)
Approximation and learning of anisotropic and mixed smooth functions by deep ReLU neural networks
par: Yang, Yunfei, et autres
Publié: (2026)
par: Yang, Yunfei, et autres
Publié: (2026)
Cell-induced densification and tether formation in fibrous extracellular matrices with biomimetic physics-informed neural networks
par: Lin, Anci, et autres
Publié: (2026)
par: Lin, Anci, et autres
Publié: (2026)
A shallow physics-informed neural network for solving partial differential equations on surfaces
par: Hu, Wei-Fan, et autres
Publié: (2022)
par: Hu, Wei-Fan, et autres
Publié: (2022)
LazyDINO: Fast, scalable, and efficiently amortized Bayesian inversion via structure-exploiting and surrogate-driven measure transport
par: Cao, Lianghao, et autres
Publié: (2024)
par: Cao, Lianghao, et autres
Publié: (2024)
Robust radial basis function interpolation based on geodesic distance for the numerical coupling of multiphysics problems
par: Bucelli, Michele, et autres
Publié: (2024)
par: Bucelli, Michele, et autres
Publié: (2024)
Approximation by non-symmetric networks for cross-domain learning
par: Mhaskar, Hrushikesh
Publié: (2023)
par: Mhaskar, Hrushikesh
Publié: (2023)
A decomposition-based robust training of physics-informed neural networks for nearly incompressible linear elasticity
par: Dick, Josef, et autres
Publié: (2025)
par: Dick, Josef, et autres
Publié: (2025)
A hybrid iterative method based on MIONet for PDEs: Theory and numerical examples
par: Hu, Jun, et autres
Publié: (2024)
par: Hu, Jun, et autres
Publié: (2024)
Robust Fuzzy local k-plane clustering with mixture distance of hinge loss and L1 norm
par: Huang, Junjun, et autres
Publié: (2026)
par: Huang, Junjun, et autres
Publié: (2026)
The functional impact of myofiber macroscopic organization and disarray in computational models of the murine heart
par: Guastamacchia, Carlo, et autres
Publié: (2026)
par: Guastamacchia, Carlo, et autres
Publié: (2026)
Long-term simulation of physical and mechanical behaviors using curriculum-transfer-learning based physics-informed neural networks
par: Guo, Yuan, et autres
Publié: (2025)
par: Guo, Yuan, et autres
Publié: (2025)
Learning solution operators of PDEs defined on varying domains via MIONet
par: Xiao, Shanshan, et autres
Publié: (2024)
par: Xiao, Shanshan, et autres
Publié: (2024)
Diffeomorphism Neural Operator for various domains and parameters of partial differential equations
par: Zhao, Zhiwei, et autres
Publié: (2024)
par: Zhao, Zhiwei, et autres
Publié: (2024)
Neural network-driven domain decomposition for efficient solutions to the Helmholtz equation
par: Dolean, Victorita, et autres
Publié: (2025)
par: Dolean, Victorita, et autres
Publié: (2025)
High precision PINNs in unbounded domains: application to singularity formulation in PDEs
par: Wang, Yixuan, et autres
Publié: (2025)
par: Wang, Yixuan, et autres
Publié: (2025)
Probabilistic operator learning: generative modeling and uncertainty quantification for foundation models of differential equations
par: Zhang, Benjamin J., et autres
Publié: (2025)
par: Zhang, Benjamin J., et autres
Publié: (2025)
Documents similaires
-
Shape-informed cardiac mechanics surrogates in data-scarce regimes via geometric encoding and generative augmentation
par: Carrara, Davide, et autres
Publié: (2026) -
A model learning framework for inferring the dynamics of transmission rate depending on exogenous variables for epidemic forecasts
par: Ziarelli, Giovanni, et autres
Publié: (2024) -
Learning geometry-dependent lead-field operators for forward ECG modeling
par: Dokuchaev, Arsenii, et autres
Publié: (2026) -
The internal law of a material can be discovered from its boundary
par: Regazzoni, Francesco
Publié: (2026) -
Physics-informed neural network estimation of active material properties in time-dependent cardiac biomechanical models
par: Höfler, Matthias, et autres
Publié: (2025)