Guardado en:
| Autor principal: | Uddin, Ziya |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2601.09567 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Exploring Physics-Informed Neural Networks: From Fundamentals to Applications in Complex Systems
por: Ganga, Sai, et al.
Publicado: (2024)
por: Ganga, Sai, et al.
Publicado: (2024)
Solving Differential Equations with Constrained Learning
por: Moro, Viggo, et al.
Publicado: (2024)
por: Moro, Viggo, et al.
Publicado: (2024)
Physics-Informed Neural Networks for Solving Contact Problems in Three Dimensions
por: Sahin, Tarik, et al.
Publicado: (2024)
por: Sahin, Tarik, et al.
Publicado: (2024)
Bridging Computational Fluid Dynamics Algorithm and Physics-Informed Learning: SIMPLE-PINN for Incompressible Navier-Stokes Equations
por: Wei, Chang, et al.
Publicado: (2026)
por: Wei, Chang, et al.
Publicado: (2026)
Physics-Informed Holomorphic Neural Networks (PIHNNs): Solving Linear Elasticity Problems
por: Calafà, Matteo, et al.
Publicado: (2024)
por: Calafà, Matteo, et al.
Publicado: (2024)
Solving Stochastic Differential Equations with Jump-Diffusion Efficiently: Applications to FPT Problems in Credit Risk
por: Zhang, Di, et al.
Publicado: (2007)
por: Zhang, Di, et al.
Publicado: (2007)
Physics Informed Neural Network using Finite Difference Method
por: Lim, Kart Leong, et al.
Publicado: (2026)
por: Lim, Kart Leong, et al.
Publicado: (2026)
Physics-Enforced Neural Ordinary Differential Equation for Chemical Kinetics Optimization in Reaction-Diffusion Systems
por: Cai, Feixue, et al.
Publicado: (2026)
por: Cai, Feixue, et al.
Publicado: (2026)
Provably Efficient Quantum Algorithms for Solving Nonlinear Differential Equations Using Multiple Bosonic Modes Coupled with Qubits
por: Gan, Yu, et al.
Publicado: (2025)
por: Gan, Yu, et al.
Publicado: (2025)
Physics-Informed Machine Learning for Battery Degradation Diagnostics: A Comparison of State-of-the-Art Methods
por: Navidi, Sina, et al.
Publicado: (2024)
por: Navidi, Sina, et al.
Publicado: (2024)
Adaptive Finite State Projection with Quantile-Based Pruning for Solving the Chemical Master Equation
por: Dendukuri, Aditya, et al.
Publicado: (2025)
por: Dendukuri, Aditya, et al.
Publicado: (2025)
Universal Differential Equations as a Common Modeling Language for Neuroscience
por: ElGazzar, Ahmed, et al.
Publicado: (2024)
por: ElGazzar, Ahmed, et al.
Publicado: (2024)
Enforced Interface Constraints for Domain Decomposition Method of Discrete Physics-Informed Neural Networks
por: Yin, Jichao, et al.
Publicado: (2025)
por: Yin, Jichao, et al.
Publicado: (2025)
Optimal Box Contraction for Solving Linear Systems via Simulated and Quantum Annealing
por: Suresh, Sanjay, et al.
Publicado: (2024)
por: Suresh, Sanjay, et al.
Publicado: (2024)
A Dual Physics-Informed Kolmogorov-Arnold Neural Network Framework for Continuum Topology Optimization
por: Zhang, Junyuan, et al.
Publicado: (2026)
por: Zhang, Junyuan, et al.
Publicado: (2026)
A Physics-Informed Neural Network Framework for Simulating Creep Buckling in Growing Viscoelastic Biological Tissues
por: Lin, Zhongya, et al.
Publicado: (2025)
por: Lin, Zhongya, et al.
Publicado: (2025)
An Agentic AI Workflow to Simplify Parameter Estimation of Complex Differential Equation Systems
por: Bhatnagar, Saakaar
Publicado: (2025)
por: Bhatnagar, Saakaar
Publicado: (2025)
Towards a Hybrid Digital Twin: Physics-Informed Neural Networks as Surrogate Model of a Reinforced Concrete Beam
por: Sahin, Tarik, et al.
Publicado: (2024)
por: Sahin, Tarik, et al.
Publicado: (2024)
Quantum Homotopy Algorithm for Solving Nonlinear PDEs and Flow Problems
por: Bharadwaj, Sachin S., et al.
Publicado: (2025)
por: Bharadwaj, Sachin S., et al.
Publicado: (2025)
GeoMCP: A Trustworthy Framework for AI-Assisted Analytical Geotechnical Engineering
por: Bekele, Yared W.
Publicado: (2026)
por: Bekele, Yared W.
Publicado: (2026)
Physics-informed Deep Learning to Solve Three-dimensional Terzaghi Consolidation Equation: Forward and Inverse Problems
por: Yuan, Biao, et al.
Publicado: (2024)
por: Yuan, Biao, et al.
Publicado: (2024)
Investigation on the Shooting Method Ability to Solve Different Mooring Lines Boundary Condition Types
por: Surmont, Florian, et al.
Publicado: (2024)
por: Surmont, Florian, et al.
Publicado: (2024)
Solving Electromagnetic Scattering Problems by Isogeometric Analysis with Deep Operator Learning
por: Backmeyer, Merle, et al.
Publicado: (2024)
por: Backmeyer, Merle, et al.
Publicado: (2024)
TOFLUX: A Differentiable Topology Optimization Framework for Multiphysics Fluidic Problems
por: Padhy, Rahul Kumar, et al.
Publicado: (2025)
por: Padhy, Rahul Kumar, et al.
Publicado: (2025)
Physics-Informed Video Diffusion For Shallow Water Equations
por: Bai, Yang, et al.
Publicado: (2026)
por: Bai, Yang, et al.
Publicado: (2026)
Perturbative Analytical Framework for Thermal Wave Diffusion in Non-linear Building Envelopes
por: Guigot, Corentin
Publicado: (2026)
por: Guigot, Corentin
Publicado: (2026)
Solving strategies for data-driven one-dimensional elasticity exhibiting nonlinear strains
por: Nguyen, Thi-Hoa, et al.
Publicado: (2025)
por: Nguyen, Thi-Hoa, et al.
Publicado: (2025)
PRIMAD-LID: A Developed Framework for Computational Reproducibility
por: Aloqalaa, Meznah, et al.
Publicado: (2026)
por: Aloqalaa, Meznah, et al.
Publicado: (2026)
Deep Feynman-Kac Methods for High-dimensional Semilinear Parabolic Equations: Revisit
por: Zheng, Xiaotao, et al.
Publicado: (2025)
por: Zheng, Xiaotao, et al.
Publicado: (2025)
A Taxonomy of Numerical Differentiation Methods
por: Komarov, Pavel, et al.
Publicado: (2025)
por: Komarov, Pavel, et al.
Publicado: (2025)
PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks
por: Zhao, Zhiyuan, et al.
Publicado: (2023)
por: Zhao, Zhiyuan, et al.
Publicado: (2023)
Isogeometric Shape Optimization of Multi-Tapered Coaxial Baluns Simulated by an Integral Equation Method
por: Balouchev, Boian, et al.
Publicado: (2024)
por: Balouchev, Boian, et al.
Publicado: (2024)
Hybridized Projected Differential Transform Method For collisional-breakage equation
por: Shweta, et al.
Publicado: (2024)
por: Shweta, et al.
Publicado: (2024)
Modern, Efficient, and Differentiable Transport Equation Models using JAX: Applications to Population Balance Equations
por: Alsubeihi, Mohammed, et al.
Publicado: (2024)
por: Alsubeihi, Mohammed, et al.
Publicado: (2024)
Training Stiff Neural Ordinary Differential Equations with Implicit Single-Step Methods
por: Fronk, Colby, et al.
Publicado: (2024)
por: Fronk, Colby, et al.
Publicado: (2024)
A Monolithic Computational Homogenization Framework for Nearly Incompressible Magnetoelastic Composites
por: Spencer, L. River, et al.
Publicado: (2026)
por: Spencer, L. River, et al.
Publicado: (2026)
I-FENN for thermoelasticity based on physics-informed temporal convolutional network (PI-TCN)
por: Abueidda, Diab W., et al.
Publicado: (2023)
por: Abueidda, Diab W., et al.
Publicado: (2023)
On a High-Frequency Analysis of Some Relevant Integral Equations in Electromagnetics
por: Giunzioni, V., et al.
Publicado: (2024)
por: Giunzioni, V., et al.
Publicado: (2024)
A Concept for Autonomous Problem-Solving in Intralogistics Scenarios
por: Sigel, Johannes, et al.
Publicado: (2025)
por: Sigel, Johannes, et al.
Publicado: (2025)
Exascale Implicit Kinetic Plasma Simulations on El~Capitan for Solving the Micro-Macro Coupling in Magnetospheric Physics
por: Markidis, Stefano, et al.
Publicado: (2025)
por: Markidis, Stefano, et al.
Publicado: (2025)
Ejemplares similares
-
Exploring Physics-Informed Neural Networks: From Fundamentals to Applications in Complex Systems
por: Ganga, Sai, et al.
Publicado: (2024) -
Solving Differential Equations with Constrained Learning
por: Moro, Viggo, et al.
Publicado: (2024) -
Physics-Informed Neural Networks for Solving Contact Problems in Three Dimensions
por: Sahin, Tarik, et al.
Publicado: (2024) -
Bridging Computational Fluid Dynamics Algorithm and Physics-Informed Learning: SIMPLE-PINN for Incompressible Navier-Stokes Equations
por: Wei, Chang, et al.
Publicado: (2026) -
Physics-Informed Holomorphic Neural Networks (PIHNNs): Solving Linear Elasticity Problems
por: Calafà, Matteo, et al.
Publicado: (2024)