Imagen de Portada

Physics-Informed DeepONet Coupled with FEM for Convective Transport in Porous Media with Sharp Gaussian Sources

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Kara, Erdi, Stinis, Panos
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

What do physics-informed DeepONets learn? Understanding and improving training for scientific computing applications
por: Williams, Emily, et al.
Publicado: (2024)

Separable DeepONet: Breaking the Curse of Dimensionality in Physics-Informed Machine Learning
por: Mandl, Luis, et al.
Publicado: (2024)

DeepONet for Solving Nonlinear Partial Differential Equations with Physics-Informed Training
por: Yang, Yahong
Publicado: (2024)

Alpha-VI DeepONet: A prior-robust variational Bayesian approach for enhancing DeepONets with uncertainty quantification
por: Lone, Soban Nasir, et al.
Publicado: (2024)

Learning Hamiltonian Density Using DeepONet
por: Xu, Baige, et al.
Publicado: (2025)

Physics-Informed DeepONets for drift-diffusion on metric graphs: simulation and parameter identification
por: Blechschmidt, Jan, et al.
Publicado: (2025)

BP-DeepONet: A new method for cuffless blood pressure estimation using the physcis-informed DeepONet
por: Li, Lingfeng, et al.
Publicado: (2024)

Efficient Transformer-Inspired Variants of Physics-Informed Deep Operator Networks
por: Wei, Zhi-Feng, et al.
Publicado: (2025)

Ensemble and Mixture-of-Experts DeepONets For Operator Learning
por: Sharma, Ramansh, et al.
Publicado: (2024)

DeepONet as a Multi-Operator Extrapolation Model: Distributed Pretraining with Physics-Informed Fine-Tuning
por: Zhang, Zecheng, et al.
Publicado: (2024)

SG-DeepONet: Source-generalized deep operator learning for full waveform inversion
por: Guo, Zekai, et al.
Publicado: (2024)

Physics-Informed Time-Integrated DeepONet: Temporal Tangent Space Operator Learning for High-Accuracy Inference
por: Mandl, Luis, et al.
Publicado: (2025)

Enhancing classification accuracy through chaos
por: Stinis, Panos
Publicado: (2026)

Operator Learning for Consolidation: An Architectural Comparison for DeepONet Variants
por: Choi, Yongjin, et al.
Publicado: (2025)

Improving physics-informed DeepONets with hard constraints
por: Brecht, Rüdiger, et al.
Publicado: (2023)

DeepONet-accelerated Bayesian inversion for moving boundary problems
por: Iglesias, Marco A., et al.
Publicado: (2025)

Spectral Embedding via Chebyshev Bases for Robust DeepONet Approximation
por: Abid, Muhammad, et al.
Publicado: (2025)

FEDONet : Fourier-Embedded DeepONet for Spectrally Accurate Operator Learning
por: Sojitra, Arth, et al.
Publicado: (2025)

SPIKANs: Separable Physics-Informed Kolmogorov-Arnold Networks
por: Jacob, Bruno, et al.
Publicado: (2024)

Leveraging Deep Operator Networks (DeepONet) for Acoustic Full Waveform Inversion (FWI)
por: Nath, Kamaljyoti, et al.
Publicado: (2025)

TI-DeepONet: Learnable Time Integration for Stable Long-Term Extrapolation
por: Nayak, Dibyajyoti, et al.
Publicado: (2025)

Synergistic Learning with Multi-Task DeepONet for Efficient PDE Problem Solving
por: Kumar, Varun, et al.
Publicado: (2024)

Multi-Head Residual-Gated DeepONet for Coherent Nonlinear Wave Dynamics
por: Fan, Zhiwei, et al.
Publicado: (2026)

Physics-informed DeepONet with stiffness-based loss functions for structural response prediction
por: Ahmed, Bilal, et al.
Publicado: (2024)

Shock-Aware Physics-Guided Fusion-DeepONet Operator for Rarefied Micro-Nozzle Flows
por: Roohi, Ehsan, et al.
Publicado: (2025)

Learning the Helmholtz equation operator with DeepONet for non-parametric 2D geometries
por: Barlogis, Rodolphe, et al.
Publicado: (2026)

Conformalized Quantum DeepONet Ensembles for Scalable Operator Learning with Distribution-Free Uncertainty
por: Matlia, Purav, et al.
Publicado: (2026)

NSPOD: Accelerating Krylov solvers via DeepONet-learned POD subspaces
por: Levrero-Florencio, Francesc, et al.
Publicado: (2026)

Physics-constrained DeepONet for Surrogate CFD models: a curved backward-facing step case
por: Jnini, Anas, et al.
Publicado: (2025)

Conformalized-DeepONet: A Distribution-Free Framework for Uncertainty Quantification in Deep Operator Networks
por: Moya, Christian, et al.
Publicado: (2024)

Learning Nonlinear Responses in PET Bottle Buckling with a Hybrid DeepONet-Transolver Framework
por: Kumar, Varun, et al.
Publicado: (2025)

Hybrid DeepONet Surrogates for Multiphase Flow in Porous Media
por: Santos, Ezequiel S., et al.
Publicado: (2025)

DeepONet Augmented by Randomized Neural Networks for Efficient Operator Learning in PDEs
por: Jiang, Zhaoxi, et al.
Publicado: (2025)

Efficient and generalizable nested Fourier-DeepONet for three-dimensional geological carbon sequestration
por: Lee, Jonathan E., et al.
Publicado: (2024)

fPINN-DeepONet: A Physics-Informed Operator Learning Framework for Multi-term Time-fractional Mixed Diffusion-wave Equations
por: Lu, Binghang, et al.
Publicado: (2026)

Topological DeepONets and a generalization of the Chen-Chen operator approximation theorem
por: Ismailov, Vugar
Publicado: (2026)

Quantum AS-DeepOnet: Quantum Attentive Stacked DeepONet for Solving 2D Evolution Equations
por: Wang, Hongquan, et al.
Publicado: (2026)

Hybrid twinning using PBDW and DeepONet for the effective state estimation and prediction on partially known systems
por: Massala, Stiven Briand, et al.
Publicado: (2025)

A Hybrid Conditional Diffusion-DeepONet Framework for High-Fidelity Stress Prediction in Hyperelastic Materials
por: Kota, Purna Vindhya, et al.
Publicado: (2026)

E-PINNs: Epistemic Physics-Informed Neural Networks
por: Jacob, Bruno, et al.
Publicado: (2025)