Image de couverture de livre

Physics-Informed Neural Network-based Reliability Analysis of Buried Pipelines

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Taraghi, Pouya, Li, Yong, Adeeb, Samer
Format:	Preprint
Publié:	2025
Sujets:	Computational Engineering, Finance, and Science Machine Learning Data Analysis, Statistics and Probability Applications
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Multifractality and its sources in the digital currency market
par: Drożdż, Stanisław, et autres
Publié: (2025)

Detrended cross-correlations and their random matrix limit: an example from the cryptocurrency market
par: Drożdż, Stanisław, et autres
Publié: (2025)

Markov Chain Monte Carlo with Gaussian Process Emulation for a 1D Hemodynamics Model of CTEPH
par: Kachabi, Amirreza, et autres
Publié: (2024)

Filtering amplitude dependence of correlation dynamics in complex systems: application to the cryptocurrency market
par: Wątorek, Marcin, et autres
Publié: (2025)

Correlations versus noise in the NFT market
par: Wątorek, Marcin, et autres
Publié: (2024)

Accelerating Hamiltonian Monte Carlo for Bayesian Inference in Neural Networks and Neural Operators
par: Thiagarajan, Ponkrshnan, et autres
Publié: (2025)

Characteristics of price related fluctuations in Non-Fungible Token (NFT) market
par: Szydło, Paweł, et autres
Publié: (2023)

Quantifying model prediction sensitivity to model-form uncertainty
par: Portone, Teresa, et autres
Publié: (2025)

Causal Hierarchy in the Financial Market Network -- Uncovered by the Helmholtz-Hodge-Kodaira Decomposition
par: Wand, Tobias, et autres
Publié: (2024)

Coarse graining correlation matrices according to macrostructures: Financial markets as a paradigm
par: Martínez-Ramos, M. Mijaíl, et autres
Publié: (2024)

On the performance of sequential Bayesian update for database of diverse tsunami scenarios
par: Nomura, Reika, et autres
Publié: (2024)

Reservoir Static Property Estimation Using Nearest-Neighbor Neural Network
par: Wang, Yuhe
Publié: (2024)

Machine learning for modelling unstructured grid data in computational physics: a review
par: Cheng, Sibo, et autres
Publié: (2025)

Toward Model-Agnostic Detection of New Physics Using Data-Driven Signal Regions
par: Yi, Soheun, et autres
Publié: (2024)

From Occurrence to Consequence: A Comprehensive Data-driven Analysis of Building Fire Risk
par: Ma, Chenzhi, et autres
Publié: (2025)

Combination of operational modal analysis algorithms to identify modal parameters of an actual centrifugal compressor
par: Zague, Leandro O., et autres
Publié: (2024)

Parameter estimation of structural dynamics with neural operators enabled surrogate modeling
par: Zhou, Mingyuan, et autres
Publié: (2024)

Potential-energy gating for robust state estimation in bistable stochastic systems
par: Simeone, Luigi
Publié: (2026)

Integrating Bayesian Spectral Deconvolution and Expert Scientific Reasoning for Robust Peak Estimation
par: Okubo, Hayato, et autres
Publié: (2026)

History Matching under Uncertainty of Geological Scenarios with Implicit Geological Realism Control with Generative Deep Learning and Graph Convolutions
par: Shishaev, Gleb, et autres
Publié: (2025)

GeoConformal prediction: a model-agnostic framework of measuring the uncertainty of spatial prediction
par: Lou, Xiayin, et autres
Publié: (2024)

Surrogate Modelling of Proton Dose with Monte Carlo Dropout Uncertainty Quantification
par: Pim, Aaron, et autres
Publié: (2025)

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

Evaluation of Performance Measures for Qualifying Flood Models with Satellite Observations
par: Travert, Jean-Paul, et autres
Publié: (2024)

Learning Likelihood Ratios with Neural Network Classifiers
par: Rizvi, Shahzar, et autres
Publié: (2023)

A geometry-aligned multi-fidelity framework for uncertainty quantification of wildfire spread
par: Vogiatzoglou, Konstantinos, et autres
Publié: (2026)

Control Co-Design Under Uncertainty for Offshore Wind Farms: Optimizing Grid Integration, Energy Storage, and Market Participation
par: Sharma, Himanshu, et autres
Publié: (2025)

Stochastic Subspace via Probabilistic Principal Component Analysis for Characterizing Model Error
par: Yadav, Akash, et autres
Publié: (2025)

Machine Learning-Assisted Sustainable Remanufacturing, Reusing and Recycling for Lithium-ion Batteries
par: Tao, Shengyu
Publié: (2024)

Inherited or produced? Inferring protein production kinetics when protein counts are shaped by a cell's division history
par: Pessoa, Pedro, et autres
Publié: (2025)

Nonparametric Stochastic Subspaces via the Bootstrap for Characterizing Model Error
par: Yadav, Akash, et autres
Publié: (2025)

Visibility graphs can make money in financial markets
par: Rak, Rafał
Publié: (2026)

Certifiable Risk-Based Engineering Design Optimization
par: Chaudhuri, Anirban, et autres
Publié: (2021)

A Tutorial on Bayesian Analysis of Linear Shock Compression Data
par: Bernstein, Jason, et autres
Publié: (2026)

Inferring Grain Size Distributions from Magnetic Hysteresis in M-type Hexaferrites
par: Ataei, Masoud, et autres
Publié: (2025)

What are You Weighting For? Improved Weights for Gaussian Mixture Filtering With Application to Cislunar Orbit Determination
par: Durant, Dalton, et autres
Publié: (2024)

Model-based and empirical analyses of stochastic fluctuations in economy and finance
par: Zadourian, Rubina
Publié: (2024)

Smart Ensemble Learning Framework for Predicting Groundwater Heavy Metal Pollution
par: Ansah-Narh, T., et autres
Publié: (2026)

EnScale: Temporally-consistent multivariate generative downscaling via proper scoring rules
par: Schillinger, Maybritt, et autres
Publié: (2025)

Titanic overconfidence -- dark uncertainty can sink hybrid metrology for semiconductor manufacturing
par: Dixson, Ronald G., et autres
Publié: (2026)