Cover Image

Proper Latent Decomposition

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kelshaw, Daniel, Magri, Luca
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Fluid Dynamics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Physics-constrained convolutional neural networks for inverse problems in spatiotemporal partial differential equations
by: Kelshaw, Daniel, et al.
Published: (2024)

Decoder Decomposition for the Analysis of the Latent Space of Nonlinear Autoencoders With Wind-Tunnel Experimental Data
by: Mo, Yaxin, et al.
Published: (2024)

Reconstructing unsteady flows from sparse, noisy measurements with a physics-constrained convolutional neural network
by: Mo, Yaxin, et al.
Published: (2024)

Online model learning with data-assimilated reservoir computers
by: Nóvoa, Andrea, et al.
Published: (2025)

Efficient Real-Time Adaptation of ROMs for Unsteady Flows Using Data Assimilation
by: Zighed, Ismaël, et al.
Published: (2026)

Data-Assimilated Model-Based Reinforcement Learning for Partially Observed Chaotic Flows
by: Ozan, Defne E., et al.
Published: (2025)

Lost in Latent Space: An Empirical Study of Latent Diffusion Models for Physics Emulation
by: Rozet, François, et al.
Published: (2025)

Lagrangian Proper Orthogonal Decomposition
by: Shnapp, Ron, et al.
Published: (2026)

Analysis of tidal flows through the Strait of Gibraltar using Dynamic Mode Decomposition
by: Dias, Sathsara, et al.
Published: (2023)

Variational Mode Decomposition-Based Nonstationary Coherent Structure Analysis for Spatiotemporal Data
by: Ohmichi, Yuya
Published: (2023)

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

Koopman Autoencoders with Continuous-Time Latent Dynamics for Fluid Dynamics Forecasting
by: Grozavescu, Rares, et al.
Published: (2026)

LAViG-FLOW: Latent Autoregressive Video Generation for Fluid Flow Simulations
by: De Pellegrini, Vittoria, et al.
Published: (2026)

Towards extreme event prediction of turbulent flows with quantized local reduced-order models
by: Colanera, Antonio, et al.
Published: (2025)

Reconstruction of three-dimensional turbulent flows from sparse and noisy planar measurements: A weight-sharing neural network approach
by: Mo, Yaxin, et al.
Published: (2025)

CoNFiLD-inlet: Synthetic Turbulence Inflow Using Generative Latent Diffusion Models with Neural Fields
by: Liu, Xin-Yang, et al.
Published: (2024)

Component-Based Machine Learning for Indoor Flow and Temperature Fields Prediction Latent Feature Aggregation and Flow Interaction
by: Wang, Shaofan, et al.
Published: (2025)

Precursors of extreme events and critical transitions
by: Consonni, Riccardo, et al.
Published: (2026)

Parametric Dynamic Mode Decomposition with multi-linear interpolation for prediction of thermal fields of Al2O3-water nanofluid flows at unseen parameters
by: S, Abhijith M, et al.
Published: (2025)

Band-Ensemble Spectral Proper Orthogonal Decomposition with Frequency Attribution
by: von Saldern, Jakob G. R., et al.
Published: (2026)

A Fast Spectral Formulation of the Multiscale Proper Orthogonal Decomposition
by: Belda, Marek, et al.
Published: (2026)

A Physics-Informed Spatiotemporal Deep Learning Framework for Turbulent Systems
by: Menicali, Luca, et al.
Published: (2025)

Data-driven computation of adjoint sensitivities without adjoint solvers: An application to thermoacoustics
by: Ozan, Defne E., et al.
Published: (2024)

Hard-constrained neural networks for modelling nonlinear acoustics
by: Ozan, Defne Ege, et al.
Published: (2023)

LatentFlow: Cross-Frequency Experimental Flow Reconstruction from Sparse Pressure via Latent Mapping
by: Liu, Junle, et al.
Published: (2025)

CFDTwin: An open-source GUI and Python toolkit for POD-NN surrogate modeling of ANSYS Fluent simulations
by: Curl, Daniel, et al.
Published: (2026)

Knowledge-Based Convolutional Neural Network for the Simulation and Prediction of Two-Phase Darcy Flows
by: Elabid, Zakaria, et al.
Published: (2024)

Physics-constrained coupled neural differential equations for one dimensional blood flow modeling
by: Csala, Hunor, et al.
Published: (2024)

oRANS: Online optimisation of RANS machine learning models with embedded DNS data generation
by: Dehtyriov, Daniel, et al.
Published: (2025)

Deep Learning-based Algebraic Reynolds Stress Closures for RANS Simulations of Turbulent Flows
by: Dehtyriov, Daniel, et al.
Published: (2026)

Transported Memory Networks accelerating Computational Fluid Dynamics
by: Schulz, Matthias, et al.
Published: (2025)

Inpainting physics: self-supervised learning for context-driven fluid simulation
by: Weidner, Jonas, et al.
Published: (2026)

Computing distances and means on manifolds with a metric-constrained Eikonal approach
by: Kelshaw, Daniel, et al.
Published: (2024)

Data-driven Mori-Zwanzig modeling of Lagrangian particle dynamics in turbulent flows
by: de Wit, Xander, et al.
Published: (2025)

Predicting Wave Dynamics using Deep Learning with Multistep Integration Inspired Attention and Physics-Based Loss Decomposition
by: Deo, Indu Kant, et al.
Published: (2025)

Hilbert Proper Orthogonal Decomposition: a tool for educing advective wavepackets from flow field data
by: Raiola, Marco, et al.
Published: (2025)

HiLiftAeroML: High-Fidelity Computational Fluid Dynamics Dataset for High-Lift Aircraft Aerodynamics
by: Ashton, Neil, et al.
Published: (2026)

Neural Operator-Based Proxy for Reservoir Simulations Considering Varying Well Settings, Locations, and Permeability Fields
by: Badawi, Daniel, et al.
Published: (2024)

Stochastic Reconstruction of Gappy Lagrangian Turbulent Signals by Conditional Diffusion Models
by: Li, Tianyi, et al.
Published: (2024)

The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning
by: Ohana, Ruben, et al.
Published: (2024)