Buchumschlag

Generative Adversarial Reduced Order Modelling

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Coscia, Dario, Demo, Nicola, Rozza, Gianluigi
Format:	Preprint
Veröffentlicht:	2023
Schlagworte:	Machine Learning Numerical Analysis
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Towards a machine learning pipeline in reduced order modelling for inverse problems: neural networks for boundary parametrization, dimensionality reduction and solution manifold approximation
von: Ivagnes, Anna, et al.
Veröffentlicht: (2022)

An extended physics informed neural network for preliminary analysis of parametric optimal control problems
von: Demo, Nicola, et al.
Veröffentlicht: (2021)

A Dimensionality Reduction Approach for Convolutional Neural Networks
von: Meneghetti, Laura, et al.
Veröffentlicht: (2021)

A Shape Optimization Pipeline for Marine Propellers by means of Reduced Order Modeling Techniques
von: Ivagnes, Anna, et al.
Veröffentlicht: (2023)

A Proper Orthogonal Decomposition approach for parameters reduction of Single Shot Detector networks
von: Meneghetti, Laura, et al.
Veröffentlicht: (2022)

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling
von: Padula, Guglielmo, et al.
Veröffentlicht: (2025)

Gaussian process approach within a data-driven POD framework for fluid dynamics engineering problems
von: Ortali, Giulio, et al.
Veröffentlicht: (2020)

Machine Learning-based quadratic closures for non-intrusive Reduced Order Models
von: Codega, Gabriele, et al.
Veröffentlicht: (2025)

Model Order Reduction of Cerebrovascular Hemodynamics Using POD_Galerkin and Reservoir Computing_based Approach
von: Halder, Rahul, et al.
Veröffentlicht: (2026)

BARNN: A Bayesian Autoregressive and Recurrent Neural Network
von: Coscia, Dario, et al.
Veröffentlicht: (2025)

Deep Reinforcement Learning for the Heat Transfer Control of Pulsating Impinging Jets
von: Salavatidezfouli, Sajad, et al.
Veröffentlicht: (2023)

A local approach to parameter space reduction for regression and classification tasks
von: Romor, Francesco, et al.
Veröffentlicht: (2021)

Latent Dynamics Graph Convolutional Networks for model order reduction of parameterized time-dependent PDEs
von: Tomada, Lorenzo, et al.
Veröffentlicht: (2026)

Non-intrusive model reduction of advection-dominated hyperbolic problems using neural network shift augmented manifold transformation
von: Gowrachari, Harshith, et al.
Veröffentlicht: (2024)

A brief review of Reduced Order Models using intrusive and non-intrusive techniques
von: Padula, Guglielmo, et al.
Veröffentlicht: (2024)

Time Extrapolation with Graph Convolutional Autoencoder and Tensor Train Decomposition
von: Chen, Yuanhong, et al.
Veröffentlicht: (2025)

Data-driven Closure Strategies for Parametrized Reduced Order Models via Deep Operator Networks
von: Ivagnes, Anna, et al.
Veröffentlicht: (2025)

An efficient computational framework for naval shape design and optimization problems by means of data-driven reduced order modeling techniques
von: Demo, Nicola, et al.
Veröffentlicht: (2020)

Enhancing non-intrusive Reduced Order Models with space-dependent aggregation methods
von: Ivagnes, Anna, et al.
Veröffentlicht: (2024)

Parametric Intrusive Reduced Order Models enhanced with Machine Learning Correction Terms
von: Ivagnes, Anna, et al.
Veröffentlicht: (2024)

Optimisation-Based Coupling of Finite Element Model and Reduced Order Model for Computational Fluid Dynamics
von: Prusak, Ivan, et al.
Veröffentlicht: (2024)

Integrating Artificial Intelligence, Physics, and Internet of Things: A Framework for Cultural Heritage Conservation
von: Valentino, Carmine, et al.
Veröffentlicht: (2026)

A Dynamic Mode Decomposition Extension for the Forecasting of Parametric Dynamical Systems
von: Andreuzzi, Francesco, et al.
Veröffentlicht: (2021)

Introduction to the Combination of Reduced Order Models and Domain Decomposition: State of the Art and Perspectives
von: Ruan, Shenhui, et al.
Veröffentlicht: (2026)

Data-driven Discovery of Delay Differential Equations with Discrete Delays
von: Pecile, Alessandro, et al.
Veröffentlicht: (2024)

Physics Informed Neural Network Framework for Unsteady Discretized Reduced Order System
von: Halder, Rahul, et al.
Veröffentlicht: (2023)

A hybrid Reduced Order Model to enforce outflow pressure boundary conditions in computational haemodynamics
von: Siena, Pierfrancesco, et al.
Veröffentlicht: (2025)

Stabilized POD Reduced Order Models for convection-dominated incompressible flows
von: Siena, Pierfrancesco, et al.
Veröffentlicht: (2024)

Combining Extended Convolutional Autoencoders and Reservoir Computing for Accurate Reduced-Order Predictions of Atmospheric Flows
von: Hajisharifi, Arash, et al.
Veröffentlicht: (2025)

Efficient and Accurate Surrogate Modeling of Turbulent Flows via Space-Dependent Aggregation and Reduced Order Models
von: Zappi, Piero, et al.
Veröffentlicht: (2026)

Optimized Bayesian Framework for Inverse Heat Transfer Problems Using Reduced Order Methods
von: Bakhshaei, Kabir, et al.
Veröffentlicht: (2024)

KROM: Kernelized Reduced Order Modeling
von: Bacho, Aras, et al.
Veröffentlicht: (2026)

A Predictive Surrogate Model for Heat Transfer of an Impinging Jet on a Concave Surface
von: Salavatidezfouli, Sajad, et al.
Veröffentlicht: (2024)

A Review of Equation-Based and Data-Driven Reduced Order Models featuring a Hybrid cardiovascular application
von: Siena, Pierfrancesco, et al.
Veröffentlicht: (2025)

A Multi-Fidelity Parametric Framework for Reduced-Order Modeling using Optimal Transport-based Interpolation: Applications to Diffused-Interface Two-Phase Flows
von: Khamlich, Moaad, et al.
Veröffentlicht: (2026)

Model Reduction for Transport-Dominated Problems via Cross-Correlation Based Snapshot Registration
von: Gowrachari, Harshith, et al.
Veröffentlicht: (2025)

Higher Order Reduced Rank Regression
von: Greenberg, Leia, et al.
Veröffentlicht: (2025)

Mesh-Informed Reduced Order Models for Aneurysm Rupture Risk Prediction
von: D'Inverno, Giuseppe Alessio, et al.
Veröffentlicht: (2024)

On Geometry Regularization in Autoencoder Reduced-Order Models with Latent Neural ODE Dynamics
von: Osipov, Mikhail
Veröffentlicht: (2026)

Genetic Column Generation for Computing Lower Bounds for Adversarial Classification
von: Penka, Maximilian
Veröffentlicht: (2024)