Cover Image

Late Fusion Neural Operators for Extrapolation Across Parameter Space in Partial Differential Equations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	van Tegelen, Eva, Kapoor, Taniya, van Voorn, George A. K., van Heijster, Peter, Athanasiadis, Ioannis N.
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence Dynamical Systems
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Neural Ordinary Differential Equations for Learning and Extrapolating System Dynamics Across Bifurcations
by: van Tegelen, Eva, et al.
Published: (2025)

Stability of asymptotic waves in the Fisher-Stefan equation
by: Bui, T. T. H., et al.
Published: (2024)

GS-PINN: Greedy Sampling for Parameter Estimation in Partial Differential Equations
by: Forootani, Ali, et al.
Published: (2024)

Chaotic motion and singularity structures of front solutions in multi-component FitzHugh-Nagumo-type systems
by: Chirilus-Bruckner, Martina, et al.
Published: (2024)

Physics-Informed Chebyshev Polynomial Neural Operator for Parametric Partial Differential Equations
by: Chen, Biao, et al.
Published: (2026)

Existence of Invariant Probability Measures for Stochastic Differential Equations with Finite Time Delay
by: Bosch, Mark van den, et al.
Published: (2024)

GN-SINDy: Greedy Sampling Neural Network in Sparse Identification of Nonlinear Partial Differential Equations
by: Forootani, Ali, et al.
Published: (2024)

Deformations of acid-mediated invasive tumors in a model with Allee effect
by: Carter, Paul, et al.
Published: (2024)

Stochastic Wright's Equation: Existence of Invariant Measures
by: Bosch, Mark van den, et al.
Published: (2026)

Stochastic Mackey-Glass Equations and Other Negative Feedback Systems: Existence of Invariant Measures
by: Bosch, Mark van den, et al.
Published: (2026)

Differentiable Autoencoding Neural Operator for Interpretable and Integrable Latent Space Modeling
by: Viknesh, Siva, et al.
Published: (2025)

Lie Generator Networks for Nonlinear Partial Differential Equations
by: Jamil, Shafayeth, et al.
Published: (2026)

Partial Eigenvalue Assignment for Nonlinear Systems
by: Wang, Shang, et al.
Published: (2025)

Automating the Discovery of Partial Differential Equations in Dynamical Systems
by: Li, Weizhen, et al.
Published: (2024)

A Birkhoff Normal Form Theorem for Partial Differential Equations on torus
by: Liu, Jianjun, et al.
Published: (2024)

Dual Representations and $H_{\infty}$-Optimal Control of Partial Differential Equations
by: Shivakumar, Sachin, et al.
Published: (2022)

Fusion-DeepONet: A Data-Efficient Neural Operator for Geometry-Dependent Hypersonic and Supersonic Flows
by: Peyvan, Ahmad, et al.
Published: (2025)

A Neural-Operator Surrogate for Platelet Deformation Across Capillary Numbers
by: Laudato, Marco
Published: (2025)

Boundary Treatment for Variational Quantum Simulations of Partial Differential Equations on Quantum Computers
by: Over, Paul, et al.
Published: (2024)

Quadratization of Autonomous Partial Differential Equations: Theory and Algorithms
by: Olivieri, Albani, et al.
Published: (2026)

Thermodynamics of surfactant-enriched binary-fluid systems
by: van Sluijs, T. B., et al.
Published: (2024)

Continuation for Nonlinear Elliptic Partial Differential Equations Discretized by the Multiquadric Method
by: Fedoseyev, A. I., et al.
Published: (1998)

Neural Integral Equations
by: Zappala, Emanuele, et al.
Published: (2022)

Time and State Dependent Neural Delay Differential Equations
by: Monsel, Thibault, et al.
Published: (2023)

Fourier Series-Based Approximation of Time-Varying Parameters in Ordinary Differential Equations
by: Fitzpatrick, Anna, et al.
Published: (2021)

On the Consistency of Dynamic Wetting Boundary Conditions for the Navier-Stokes-Cahn-Hilliard Equations
by: Demont, T. H. B., et al.
Published: (2024)

Critical Slowing Down in Bifurcating Stochastic Partial Differential Equations with Red Noise
by: Bernuzzi, Paolo, et al.
Published: (2025)

Linear-Nonlinear Fusion Neural Operator for Partial Differential Equations
by: Wu, Heng, et al.
Published: (2026)

On Data-Driven Unbiased Predictors using the Koopman Operator
by: Schurig, Roland, et al.
Published: (2026)

Neural Ordinary Differential Equations for Modeling Socio-Economic Dynamics
by: Samota, Sandeep Kumar, et al.
Published: (2026)

Data-Specific Hyper-Parameter Design: A Paradigm Shift in Reservoir Computing
by: Manjunath, G, et al.
Published: (2026)

Observability and State Estimation for Smooth and Nonsmooth Differential Algebraic Equation Systems
by: Abdelfattah, Hesham, et al.
Published: (2025)

Rigorous Numerics for Partial Differential Equations: the Kuramoto-Sivashinsky equation
by: Zgliczynski, P., et al.
Published: (2000)

Embedded Variational Neural Stochastic Differential Equations for Learning Heterogeneous Dynamics
by: Samota, Sandeep Kumar, et al.
Published: (2026)

$PG-NODE^{TB}$: Physics-Guided Neural Ordinary Differential Equations for Tuberculosis Transmission Dynamics
by: Kasereka, Selain K., et al.
Published: (2026)

Understanding Latent Timescales in Neural Ordinary Differential Equation Models for Advection-Dominated Dynamical Systems
by: Nair, Ashish S., et al.
Published: (2024)

Trapping and extreme clustering of finitely-dense inertial particles near a rotating vortex pair
by: Kapoor, Saumav, et al.
Published: (2024)

MixINN: Accelerating Plant Breeding by Combining Mixed Models and Deep Learning for Interaction Prediction
by: Potze, Aike, et al.
Published: (2026)

Filtered Partial Differential Equations: a robust surrogate constraint in physics-informed deep learning framework
by: Zhang, Dashan, et al.
Published: (2023)

Implicit Boundary Conditions in Partial Differential Equations Discretizations: Identifying Spurious Modes and Model Reduction
by: Karam, Pascal R, et al.
Published: (2023)