Imagen de Portada

Efficient and generalizable nested Fourier-DeepONet for three-dimensional geological carbon sequestration

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Lee, Jonathan E., Zhu, Min, Xi, Ziqiao, Wang, Kun, Yuan, Yanhua O., Lu, Lu
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Computational Physics
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Fourier-DeepONet: Fourier-enhanced deep operator networks for full waveform inversion with improved accuracy, generalizability, and robustness
por: Zhu, Min, et al.
Publicado: (2023)

Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration
por: Jiang, Zhongyi, et al.
Publicado: (2023)

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

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)

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

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

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

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)

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

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

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

DD-DeepONet: Domain decomposition and DeepONet for solving partial differential equations in three application scenarios
por: Yang, Bo, et al.
Publicado: (2025)

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

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

Hybrid Least Squares/Gradient Descent Methods for DeepONets
por: Choi, Jun, et al.
Publicado: (2025)

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

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

Quantum DeepONet: Neural operators accelerated by quantum computing
por: Xiao, Pengpeng, et al.
Publicado: (2024)

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

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

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

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

Fusion-DeepONet: A Data-Efficient Neural Operator for Geometry-Dependent Hypersonic and Supersonic Flows
por: Peyvan, Ahmad, 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)

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

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

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

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

The Calderón's problem via DeepONets
por: Castro, Javier, et al.
Publicado: (2022)

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

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

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

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

ELM-DeepONets: Backpropagation-Free Training of Deep Operator Networks via Extreme Learning Machines
por: Son, Hwijae
Publicado: (2025)

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)

Physics-Informed DeepONet Coupled with FEM for Convective Transport in Porous Media with Sharp Gaussian Sources
por: Kara, Erdi, et al.
Publicado: (2025)