Copertina

Attention-based Multi-fidelity Machine Learning Model for Computational Fractional Flow Reserve Assessment

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Yang, Haizhou, Figueroa, C. Alberto, Garikipati, Krishna
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Computational Engineering, Finance, and Science
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A Multi-physics Model of Flow from Coronary Angiography: Insights to Microvascular Function
di: Yang, Haizhou, et al.
Pubblicazione: (2024)

Assessing Coronary Microvascular Dysfunction using Angiography-based Data-driven Methods
di: Yang, Haizhou, et al.
Pubblicazione: (2025)

Graph Laplacian-based Bayesian Multi-fidelity Modeling
di: Pinti, Orazio, et al.
Pubblicazione: (2024)

$μ$-FlowNet: A Deep Learning Approach for Mapping Flow Fields in Irregular Microchannels Using an Attention-based U-Net Encoder-Decoder Architecture
di: Meshram, Ganesh Sahadeo, et al.
Pubblicazione: (2026)

Multi-fidelity Batch Active Learning for Gaussian Process Classifiers
di: Cutforth, Murray, et al.
Pubblicazione: (2025)

DiffLiB: High-fidelity differentiable modeling of lithium-ion batteries and efficient gradient-based parameter identification
di: Xu, Weipeng, et al.
Pubblicazione: (2025)

Multi-fidelity Hamiltonian Monte Carlo
di: Patel, Dhruv V., et al.
Pubblicazione: (2024)

Quantum Computing for Multi Period Asset Allocation
di: Sun, Queenie, et al.
Pubblicazione: (2024)

Exploring Multi-Fidelity Aeroelastic Tailoring: Prospect and Model Assessment
di: Maathuis, Hauke, et al.
Pubblicazione: (2024)

BridgeNet: A Dataset of Graph-based Bridge Structural Models for Machine Learning Applications
di: Bleker, Lazlo, et al.
Pubblicazione: (2025)

BioXArena: Benchmarking LLM Agents on Multi-Modal Biomedical Machine Learning Tasks
di: Li, Loka, et al.
Pubblicazione: (2026)

Efficient Bayesian multi-fidelity inverse analysis for expensive and non-differentiable physics-based simulations in high stochastic dimensions
di: Nitzler, Jonas, et al.
Pubblicazione: (2025)

Interpretable Machine Learning Models for Predicting the Next Targets of Activist Funds
di: Kim, Minwu, et al.
Pubblicazione: (2024)

Efficient Aircraft Design Optimization Using Multi-Fidelity Models and Multi-fidelity Physics Informed Neural Networks
di: Sarker, Apurba
Pubblicazione: (2024)

Machine Learning (ML) based Reduced Order Modeling (ROM) for linear and non-linear solid and structural mechanics
di: Tannous, Mikhael, et al.
Pubblicazione: (2025)

D-Flow: Multi-modality Flow Matching for D-peptide Design
di: Wu, Fang, et al.
Pubblicazione: (2024)

Bi-fidelity sparse-grid interpolation driven by a local-error estimator
di: Rosellini, Matteo, et al.
Pubblicazione: (2025)

Intelligent Optimization of Mine Environmental Damage Assessment and Repair Strategies Based on Deep Learning
di: Cheng, Qishuo
Pubblicazione: (2024)

Machine Learning Approaches for Defect Detection in a Microwell-based Medical Device
di: Zhao, Xueying, et al.
Pubblicazione: (2024)

Multi-Grid Graph Neural Networks with Self-Attention for Computational Mechanics
di: Garnier, Paul, et al.
Pubblicazione: (2024)

A survey on multi-fidelity surrogates for simulators with functional outputs: unified framework and benchmark
di: Brunel, Lucas, et al.
Pubblicazione: (2024)

Blockchain-Based Trust and Transparency in Airline Reservation Systems using Microservices Architecture
di: Barua, Biman, et al.
Pubblicazione: (2024)

Temperature Prediction for Stored Grain: A Multi-model Fusion Approach Based on Machine Learning
di: Chen, Donghao, et al.
Pubblicazione: (2024)

Machine Learning-Assisted Discovery of Flow Reactor Designs
di: Savage, Tom, et al.
Pubblicazione: (2023)

Scientific Machine Learning-assisted Model Discovery from Telemetry Data
di: Micluta-Campeanu, Sebastian, et al.
Pubblicazione: (2026)

Finite Element and Machine Learning Modeling of Autogenous Self-Healing Concrete
di: Liu, William
Pubblicazione: (2025)

Machine Learning Surrogates for Optimizing Transportation Policies with Agent-Based Models
di: Natterer, Elena, et al.
Pubblicazione: (2025)

Modeling Batch Crystallization under Uncertainty Using Physics-informed Machine Learning
di: Nai, Dingqi, et al.
Pubblicazione: (2026)

LATTE: Lightweight Attention-based Traffic Accident Anticipation Engine
di: Zhang, Jiaxun, et al.
Pubblicazione: (2025)

Design optimization of semiconductor manufacturing equipment using a novel multi-fidelity surrogate modeling approach
di: Wang, Bingran, et al.
Pubblicazione: (2024)

NASPrecision: Neural Architecture Search-Driven Multi-Stage Learning for Surface Roughness Prediction in Ultra-Precision Machining
di: Ruan, Penghui, et al.
Pubblicazione: (2024)

Variational system identification of the partial differential equations governing microstructure evolution in materials: Inference over sparse and spatially unrelated data
di: Wang, Z., et al.
Pubblicazione: (2020)

PMI-DT: Leveraging Digital Twins and Machine Learning for Predictive Modeling and Inspection in Manufacturing
di: Hamel, Chas, et al.
Pubblicazione: (2024)

Gradient-Informed Machine Learning in Electromagnetics
di: Zorzetto, Matteo, et al.
Pubblicazione: (2026)

Optimizing Portfolio Management and Risk Assessment in Digital Assets Using Deep Learning for Predictive Analysis
di: Cheng, Qishuo, et al.
Pubblicazione: (2024)

A Cutting Mechanics-based Machine Learning Modeling Method to Discover Governing Equations of Machining Dynamics
di: Ren, Alisa, et al.
Pubblicazione: (2025)

Multi-fidelity Bayesian Optimization: A Review
di: Do, Bach, et al.
Pubblicazione: (2023)

Flow Field Reconstruction with Sensor Placement Policy Learning
di: Li, Ruoyan, et al.
Pubblicazione: (2026)

Designing Mechanical Meta-Materials by Learning Equivariant Flows
di: Mirramezani, Mehran, et al.
Pubblicazione: (2024)

Free-form Grid Structure Form Finding based on Machine Learning and Multi-objective Optimisation
di: Meng, Yiping, et al.
Pubblicazione: (2024)