Inverse Physics-Informed Neural Networks for transport models in porous materials
Fuente:
arXiv
Saved in:
| Main Authors: | Berardi, Marco, Difonzo, Fabio, Icardi, Matteo |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Physics Informed Neural Networks for Learning the Horizon Size in Bond-Based Peridynamic Models
by: Difonzo, Fabio V., et al.
Published: (2025)
by: Difonzo, Fabio V., et al.
Published: (2025)
Examining the robustness of Physics-Informed Neural Networks to noise for Inverse Problems
by: Jekic, Aleksandra, et al.
Published: (2025)
by: Jekic, Aleksandra, et al.
Published: (2025)
Physics Informed Neural Network Framework for Unsteady Discretized Reduced Order System
by: Halder, Rahul, et al.
Published: (2023)
by: Halder, Rahul, et al.
Published: (2023)
A reduced-order model for advection-dominated problems based on Radon Cumulative Distribution Transform
by: Long, Tobias, et al.
Published: (2023)
by: Long, Tobias, et al.
Published: (2023)
Convergence Analysis of a Spectral Numerical Method for a Peridynamic Formulation of Richards' Equation
by: Difonzo, Fabio V., et al.
Published: (2023)
by: Difonzo, Fabio V., et al.
Published: (2023)
Energy Dissipation Preserving Physics Informed Neural Network for Allen-Cahn Equations
by: Kütük, Mustafa, et al.
Published: (2024)
by: Kütük, Mustafa, et al.
Published: (2024)
Quantum-Classical Physics-Informed Neural Networks for Solving Reservoir Seepage Equations
by: Rao, Xiang, et al.
Published: (2025)
by: Rao, Xiang, et al.
Published: (2025)
From Mesh to Neural Nets: A Multi-Method Evaluation of Physics-Informed Neural Networks and Galerkin Finite Element Method for Solving Nonlinear Convection-Reaction-Diffusion Equations
by: Hasan, Fardous, et al.
Published: (2024)
by: Hasan, Fardous, et al.
Published: (2024)
Modelling parametric uncertainty in PDEs models via Physics-Informed Neural Networks
by: Panahi, Milad, et al.
Published: (2024)
by: Panahi, Milad, et al.
Published: (2024)
Nonnegative moment coordinates on finite element geometries
by: Dieci, Luca, et al.
Published: (2023)
by: Dieci, Luca, et al.
Published: (2023)
Equation Discovery, Parametric Simulation, and Optimization Using the Physics-Informed Neural Network (PINN) Method for the Heat Conduction Problem
by: Ghaderi, Ehsan, et al.
Published: (2025)
by: Ghaderi, Ehsan, et al.
Published: (2025)
HiPhom$\varepsilon$ -: HIgh order Projection-based HOMogenisation for advection diffusion reaction problems
by: Conni, Giovanni, et al.
Published: (2023)
by: Conni, Giovanni, et al.
Published: (2023)
Error Analysis and Numerical Algorithm for PDE Approximation with Hidden-Layer Concatenated Physics Informed Neural Networks
by: Qian, Yianxia, et al.
Published: (2024)
by: Qian, Yianxia, et al.
Published: (2024)
Helicity-conservative Physics-informed Neural Network Model for Navier-Stokes Equations
by: Jia, Jiwei, et al.
Published: (2022)
by: Jia, Jiwei, et al.
Published: (2022)
Bayesian Physics Informed Neural Networks for Linear Inverse problems
by: Mohammad-Djafari, Ali
Published: (2025)
by: Mohammad-Djafari, Ali
Published: (2025)
Rectangular finite elements for modeling the mechanical behavior of auxetic materials
by: Mazaev, A. V.
Published: (2024)
by: Mazaev, A. V.
Published: (2024)
HWF-PIKAN: A Multi-Resolution Hybrid Wavelet-Fourier Physics-Informed Kolmogorov-Arnold Network for solving Collisionless Boltzmann Equation
by: Heravifard, Mohammad E., et al.
Published: (2025)
by: Heravifard, Mohammad E., et al.
Published: (2025)
Plane stress finite element modelling of arbitrary compressible hyperelastic materials
by: Ahmadi, Masoud, et al.
Published: (2024)
by: Ahmadi, Masoud, et al.
Published: (2024)
Extended Physics Informed Neural Network for Hyperbolic Two-Phase Flow in Porous Media
by: Rehman, Saif Ur, et al.
Published: (2025)
by: Rehman, Saif Ur, et al.
Published: (2025)
Parameterized Physics-informed Neural Networks for Parameterized PDEs
by: Cho, Woojin, et al.
Published: (2024)
by: Cho, Woojin, et al.
Published: (2024)
Variational PINNs with tree-based integration and boundary element data in the modeling of multi-phase architected materials
by: Rodopoulos, Dimitrios C., et al.
Published: (2025)
by: Rodopoulos, Dimitrios C., et al.
Published: (2025)
Adaptive and hybrid reduced order models to mitigate Kolmogorov barrier in a multiscale kinetic transport equation
by: Jin, Tianyu, et al.
Published: (2025)
by: Jin, Tianyu, et al.
Published: (2025)
A Randomized Runge-Kutta Method for time-irregular delay differential equations
by: Difonzo, Fabio V., et al.
Published: (2024)
by: Difonzo, Fabio V., et al.
Published: (2024)
Extremization to Fine Tune Physics Informed Neural Networks for Solving Boundary Value Problems
by: Thiruthummal, Abhiram Anand, et al.
Published: (2024)
by: Thiruthummal, Abhiram Anand, et al.
Published: (2024)
A Physics-Informed Neural Network approach for compartmental epidemiological models
by: Millevoi, Caterina, et al.
Published: (2023)
by: Millevoi, Caterina, et al.
Published: (2023)
Error Bounds for Physics-Informed Neural Networks in Fokker-Planck PDEs
by: Kong, Chun-Wei, et al.
Published: (2024)
by: Kong, Chun-Wei, et al.
Published: (2024)
Spectral Informed Neural Network: An Efficient and Low-Memory PINN
by: Yu, Tianchi, et al.
Published: (2024)
by: Yu, Tianchi, et al.
Published: (2024)
Solving Forward and Inverse Problems of Contact Mechanics using Physics-Informed Neural Networks
by: Sahin, T., et al.
Published: (2023)
by: Sahin, T., et al.
Published: (2023)
PAS-Net: Physics-informed Adaptive Scale Deep Operator Network
by: Mou, Changhong, et al.
Published: (2025)
by: Mou, Changhong, et al.
Published: (2025)
Inverse modeling of porous flow through deep neural networks: the case of coffee percolation
by: Barletta, Antoniorenee, et al.
Published: (2025)
by: Barletta, Antoniorenee, et al.
Published: (2025)
Coarsening and parallelism with reduction multigrids for hyperbolic Boltzmann transport
by: Dargaville, S., et al.
Published: (2024)
by: Dargaville, S., et al.
Published: (2024)
Diffusion Synthetic Acceleration for polytopic discretisations of Boltzmann transport
by: Calloo, Ansar, et al.
Published: (2026)
by: Calloo, Ansar, et al.
Published: (2026)
Stochastic Langevin Differential Inclusions with Applications to Machine Learning
by: Difonzo, Fabio V., et al.
Published: (2022)
by: Difonzo, Fabio V., et al.
Published: (2022)
On the Stability and Convergence of Physics Informed Neural Networks
by: Gazoulis, Dimitrios, et al.
Published: (2023)
by: Gazoulis, Dimitrios, et al.
Published: (2023)
Data-Guided Physics-Informed Neural Networks for Solving Inverse Problems in Partial Differential Equations
by: Zhou, Wei, et al.
Published: (2024)
by: Zhou, Wei, et al.
Published: (2024)
Solving Maxwell's equations with Non-Trainable Graph Neural Network Message Passing
by: Bakirtzis, Stefanos, et al.
Published: (2024)
by: Bakirtzis, Stefanos, et al.
Published: (2024)
A Physics-Informed Neural Network with a Modified Lorentzian Activation for Nonlocal Gradient-Flow Equations in Dynamic Density Functional Theory
by: Gourzoulidis, Dimitrios, et al.
Published: (2026)
by: Gourzoulidis, Dimitrios, et al.
Published: (2026)
PICL: Physics Informed Contrastive Learning for Partial Differential Equations
by: Lorsung, Cooper, et al.
Published: (2024)
by: Lorsung, Cooper, et al.
Published: (2024)
Design of a specimen to train path-dependent deep learning material models from a single uniaxial test: eliciting strain diversity via automatically differentiable elastoplastic topology optimization
by: Yin, Shunyu, et al.
Published: (2025)
by: Yin, Shunyu, et al.
Published: (2025)
Solving the MIT Inverse Problem by Considering Skin and Proximity Effects in Coils
by: Yazdanian, Hassan, et al.
Published: (2025)
by: Yazdanian, Hassan, et al.
Published: (2025)
Similar Items
-
Physics Informed Neural Networks for Learning the Horizon Size in Bond-Based Peridynamic Models
by: Difonzo, Fabio V., et al.
Published: (2025) -
Examining the robustness of Physics-Informed Neural Networks to noise for Inverse Problems
by: Jekic, Aleksandra, et al.
Published: (2025) -
Physics Informed Neural Network Framework for Unsteady Discretized Reduced Order System
by: Halder, Rahul, et al.
Published: (2023) -
A reduced-order model for advection-dominated problems based on Radon Cumulative Distribution Transform
by: Long, Tobias, et al.
Published: (2023) -
Convergence Analysis of a Spectral Numerical Method for a Peridynamic Formulation of Richards' Equation
by: Difonzo, Fabio V., et al.
Published: (2023)