Copertina

Multifidelity digital twin for real-time monitoring of structural dynamics in aquaculture net cages

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Katsidoniotaki, Eirini, Su, Biao, Kelasidi, Eleni, Sapsis, Themistoklis P.
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Dynamics-Informed Deep Learning for Predicting Extreme Events
di: Katsidoniotaki, Eirini, et al.
Pubblicazione: (2026)

Information FOMO: The unhealthy fear of missing out on information. A method for removing misleading data for healthier models
di: Pickering, Ethan, et al.
Pubblicazione: (2022)

Extreme Event Aware ($η$-) Learning
di: Chang, Kai, et al.
Pubblicazione: (2025)

GEN2: A Generative Prediction-Correction Framework for Long-time Emulations of Spatially-Resolved Climate Extremes
di: Wang, Mengze, et al.
Pubblicazione: (2025)

Active search for Bifurcations
di: Psarellis, Yorgos M., et al.
Pubblicazione: (2024)

A non-intrusive machine learning framework for debiasing long-time coarse resolution climate simulations and quantifying rare events statistics
di: Sorensen, Benedikt Barthel, et al.
Pubblicazione: (2024)

Bayesian dynamic mode decomposition for real-time ship motion digital twinning
di: Palma, Giorgio, et al.
Pubblicazione: (2024)

On Some Tunable Multi-fidelity Bayesian Optimization Frameworks
di: Manoj, Arjun, et al.
Pubblicazione: (2025)

Multifidelity Cross-validation
di: Renganathan, S. Ashwin, et al.
Pubblicazione: (2024)

A Novel Computer Vision Approach for Assessing Fish Responses to Intrusive Objects in Aquaculture
di: Alvheim, Hanne-Grete, et al.
Pubblicazione: (2026)

Thermodynamics-informed graph neural networks for real-time simulation of digital human twins
di: Tesán, Lucas, et al.
Pubblicazione: (2024)

Cost-informed dimensionality reduction for structural digital twin technologies
di: Hughes, Aidan J., et al.
Pubblicazione: (2024)

From large-eddy simulations to deep learning: A U-net model for fast urban canopy flow predictions
di: Vargiemezis, Themistoklis, et al.
Pubblicazione: (2025)

Multifidelity Kolmogorov-Arnold Networks
di: Howard, Amanda A., et al.
Pubblicazione: (2024)

A probabilistic framework for learning non-intrusive corrections to long-time climate simulations from short-time training data
di: Sorensen, Benedikt Barthel, et al.
Pubblicazione: (2024)

Non-Myopic Multifidelity Bayesian Optimization
di: Di Fiore, Francesco, et al.
Pubblicazione: (2022)

Multifidelity Simulation-based Inference for Computationally Expensive Simulators
di: Krouglova, Anastasia N., et al.
Pubblicazione: (2025)

Multifidelity Gaussian process regression for solving nonlinear partial differential equations
di: El-Boukkouri, Fatima-Zahrae, et al.
Pubblicazione: (2026)

Rate-Informed Discovery via Bayesian Adaptive Multifidelity Sampling
di: Sinha, Aman, et al.
Pubblicazione: (2024)

$k$NN Attention Demystified: A Theoretical Exploration for Scalable Transformers
di: Haris, Themistoklis
Pubblicazione: (2024)

Investigation on domain adaptation of additive manufacturing monitoring systems to enhance digital twin reusability
di: Xie, Jiarui, et al.
Pubblicazione: (2024)

Adaptive digital twins for predictive decision-making: Online Bayesian learning of transition dynamics
di: Varetti, Eugenio, et al.
Pubblicazione: (2025)

Physics-Aware Multifidelity Bayesian Optimization: a Generalized Formulation
di: Di Fiore, Francesco, et al.
Pubblicazione: (2023)

MAGPI: Multifidelity-Augmented Gaussian Process Inputs for Surrogate Modeling from Scarce Data
di: Rex, Atticus, et al.
Pubblicazione: (2026)

Multifidelity Surrogate Modeling of Depressurized Loss of Forced Cooling in High-temperature Gas Reactors
di: Eaheart, Meredith, et al.
Pubblicazione: (2026)

Learning Dissipative Chaotic Dynamics with Boundedness Guarantees
di: Tang, Sunbochen, et al.
Pubblicazione: (2024)

Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies
di: Vinod, Vivin, et al.
Pubblicazione: (2024)

Assessing Non-Nested Configurations of Multifidelity Machine Learning for Quantum-Chemical Properties
di: Vinod, Vivin, et al.
Pubblicazione: (2024)

QeMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules
di: Vinod, Vivin, et al.
Pubblicazione: (2024)

Constrained optimization of sensor placement for nuclear digital twins
di: Karnik, Niharika, et al.
Pubblicazione: (2023)

Multifidelity linear regression for scientific machine learning from scarce data
di: Qian, Elizabeth, et al.
Pubblicazione: (2024)

Benchmarking Data Efficiency in $Δ$-ML and Multifidelity Models for Quantum Chemistry
di: Vinod, Vivin, et al.
Pubblicazione: (2024)

Multifidelity Covariance Estimation via Regression on the Manifold of Symmetric Positive Definite Matrices
di: Maurais, Aimee, et al.
Pubblicazione: (2023)

WindMiL: Equivariant Graph Learning for Wind Loading Prediction
di: Vargiemezis, Themistoklis, et al.
Pubblicazione: (2025)

Towards Explainable Federated Learning: Understanding the Impact of Differential Privacy
di: Oliveira, Júlio, et al.
Pubblicazione: (2026)

Active transfer learning for structural health monitoring
di: Poole, J., et al.
Pubblicazione: (2025)

Optimal sequential decision-making for error propagation mitigation in digital twins
di: Najafi, Annice, et al.
Pubblicazione: (2026)

Noise Stability of Transformer Models
di: Haris, Themistoklis, et al.
Pubblicazione: (2026)

Multifidelity domain decomposition-based physics-informed neural networks and operators for time-dependent problems
di: Heinlein, Alexander, et al.
Pubblicazione: (2024)

Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data
di: Amaxilatis, Dimitrios, et al.
Pubblicazione: (2025)