:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zeng, Zhijun, Chen, Junqing, Shi, Zuoqiang
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computational Engineering, Finance, and Science Dynamical Systems 35R30, 65M32, 68T07
Online Access:	https://arxiv.org/abs/2511.12316
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Guided Flow Matching for Forward and Inverse PDE Problems with Sparse Observations: Algorithm and Theory
by: Zhang, Xifeng, et al.
Published: (2026)

Self-Supervised Angular Deblurring in Photoacoustic Reconstruction via Noisier2Inverse
by: Haltmeier, Markus, et al.
Published: (2026)

A Carleman Semi-Discrete Convexification Method Combined With Deep Learning for Electrical Impedance Tomography
by: Klibanov, Michael V., et al.
Published: (2026)

Self-adaptive physics-informed neural network for forward and inverse problems in heterogeneous porous flow
by: Aziz, Md. Abdul, et al.
Published: (2025)

From Video-to-PDE: Data-Driven Discovery of Nonlinear Dye Plume Dynamics
by: Acosta-Minoli, Cesar, et al.
Published: (2026)

High-Fidelity Modeling of Stochastic Chemical Dynamics on Complex Manifolds: A Multi-Scale SIREN-PINN Framework for the Curvature-Perturbed Ginzburg-Landau Equation
by: Chrisnanto, Julian Evan, et al.
Published: (2026)

Regularity and tailored regularization of Deep Neural Networks, with application to parametric PDEs in uncertainty quantification
by: Keller, Alexander, et al.
Published: (2025)

A Structured Neural ODE Approach for Real Time Evaluation of AC Losses in 3D Superconducting Tapes
by: Basei, Riccardo, et al.
Published: (2025)

Numerical PDE solvers outperform neural PDE solvers
by: Chatain, Patrick, et al.
Published: (2025)

Deep Operator Networks for Bayesian Parameter Estimation in PDEs
by: Raj, Amogh, et al.
Published: (2025)

A Model-Consistent Data-Driven Computational Strategy for PDE Joint Inversion Problems
by: Ren, Kui, et al.
Published: (2022)

Learning Contractive Integral Operators with Fredholm Integral Neural Operators
by: Georgiou, Kyriakos C., et al.
Published: (2026)

GoRINNs: Godunov-Riemann Informed Neural Networks for Learning Hyperbolic Conservation Laws
by: Patsatzis, Dimitrios G., et al.
Published: (2024)

Data Completion for Electrical Impedance Tomography by Conditional Diffusion Models
by: Chen, Ke, et al.
Published: (2026)

GAN-based iterative motion estimation in HASTE MRI
by: Feinler, Mathias S., et al.
Published: (2024)

Inverse Electromagnetic Scattering for Doubly-Connected Cylinders using Convolutional Neural Networks
by: Mindrinos, Leonidas, et al.
Published: (2025)

Learnable Viscosity Modulation in Physics-Informed Neural Networks for Incompressible Flow Reconstruction
by: Xu, Ke, et al.
Published: (2026)

Concurrent multi-parameter learning demonstrated on the Kuramoto-Sivashinsky equation
by: Pachev, Benjamin, et al.
Published: (2021)

The learned range test method for the inverse inclusion problem
by: Sun, Shiwei, et al.
Published: (2024)

Deep-Picard Iteration for Space-time Fractional Diffusion PDEs
by: Zeng, Zhijun, et al.
Published: (2026)

Diff-ANO: Towards Fast High-Resolution Ultrasound Computed Tomography via Conditional Consistency Models and Adjoint Neural Operators
by: Cao, Xiang, et al.
Published: (2025)

Reconstruction of heat relaxation index in phonon transport equation
by: Chen, Peiyi, et al.
Published: (2025)

Operator learning meets inverse problems: A probabilistic perspective
by: Nelsen, Nicholas H., et al.
Published: (2025)

Data assimilation via model reference adaptation for linear and nonlinear dynamical systems
by: Kaltenbach, Benedikt, et al.
Published: (2026)

Reconstructing the thermal phonon transmission coefficient at solid interfaces in the phonon transport equation
by: Gamba, Irene M, et al.
Published: (2020)

An Acoustic Inversion-Based Flow Measurement Model in 3D Hydrodynamic Systems
by: Li, Jiwei, et al.
Published: (2025)

PINNIES: An Efficient Physics-Informed Neural Network Framework to Integral Operator Problems
by: Aghaei, Alireza Afzal, et al.
Published: (2024)

Perturbation Analysis and Neural Network-Based Initial Condition Estimation for the Sine-Gordon Equation
by: Ha, Junhong, et al.
Published: (2025)

Dynamics-Encoded Deep Learning for Robust System Identification and Parameter Estimation
by: Ho, Caitlin, et al.
Published: (2024)

RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators
by: Fabiani, Gianluca, et al.
Published: (2024)

A forward scheme with machine learning for forward-backward SDEs with jumps by decoupling jumps
by: Kawai, Reiichiro, et al.
Published: (2024)

Efficient Numerical Reconstruction of Wave Equation Sources via Droplet-Induced Asymptotics
by: Hou, Shutong, et al.
Published: (2026)

Spectral-Refiner: Accurate Fine-Tuning of Spatiotemporal Fourier Neural Operator for Turbulent Flows
by: Cao, Shuhao, et al.
Published: (2024)

Numerical reconstruction of orders in coupled systems of subdiffusion equations
by: Liu, Yikan
Published: (2025)

Mathematical analysis and symmetric fractional-order reduction method for diffusion-wave equations
by: Cen, Dakang, et al.
Published: (2026)

Deep Adaptive Dimension Reduction for Bayesian Inference in Inverse Problems
by: Wang, Yueyang, et al.
Published: (2026)

Symbolic recovery of PDEs from measurement data
by: Morina, Erion, et al.
Published: (2026)

A new architecture of high-order deep neural networks that learn martingales
by: Ninomiya, Syoiti, et al.
Published: (2025)

A Speech Enhancement Method Using Fast Fourier Transform and Convolutional Autoencoder
by: Kow, Pu-Yun, et al.
Published: (2025)

The lowest-order Neural Approximated Virtual Element Method on polygonal elements
by: Berrone, Stefano, et al.
Published: (2024)