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References from Physics-informed neural operators for the in situ characterization of locally reacting sound absorbers. Local targets link to admitted publications; unresolved targets remain external evidence.
Computer simulations in room acoustics: Concepts and uncertainties
10.1121/1.4788978 · 2013 · External reference
Experimental validation and uncertainty quantification in wave-based computational room acoustics
10.1016/j.apacoust.2021.107939 · 2021 · External reference
Unresolved reference
2008 · External reference
Fluid structure interaction and admittance boundary conditions: Setup of an analytical example
10.1142/s0218396x11004274 · 2011 · External reference
Unresolved reference
1998 · External reference
Reproducibility experiments on measuring acoustical properties of rigid-frame porous media (round-robin tests)
10.1121/1.2739806 · 2007 · External reference
Deep learning-assisted two-cavity method for estimating sound propagation characteristics in porous media
10.1142/s2591728524400012 · 2025 · External reference
Unresolved reference
2003 · External reference
A wavenumber approach to quantifying the isotropy of the sound field in reverberant spaces
10.1121/1.5032194 · 2018 · External reference
Low-frequency room acoustical simulation of a small room with BEM and complex-valued surface impedances
10.1016/j.apacoust.2021.108570 · 2022 · External reference
Boundary conditions for hybrid simulations in a rectangular environment with sound-absorbing ceiling
10.1016/j.apacoust.2025.110933 · 2025 · External reference
A review of the in situ impedance and sound absorption measurement techniques
10.3813/aaa.918840 · 2015 · External reference
A comparison of three methods to calculate the surface impedance and absorption coefficient from measurements under free field or in situ conditions
10.3813/aaa.918482 · 2011 · External reference
Sound absorption estimation using the discrete complex image source method and array processing
10.1016/j.ymssp.2025.112617 · 2025 · External reference
Spatial Fourier transform method of measuring reflection coefficients at oblique incidence. I: Theory and numerical examples
10.1121/1.400068 · 1990 · External reference
Comparison of two microphone array geometries for surface impedance estimation
10.1121/1.5116705 · 2019 · External reference
In situ acoustic characterization of a locally reacting porous material by means of PU measurement and model fitting
10.1016/j.apacoust.2022.108669 · 2022 · External reference
Estimation and minimization of errors caused by sample size effect in the measurement of the normal absorption coefficient of a locally reactive surface
10.1016/j.apacoust.2011.09.010 · 2012 · External reference
Estimation of angle-dependent absorption coefficients from spatially distributed in situ measurements
10.1121/10.0000716 · 2020 · External reference
Reverberation-chamber measurement of angle-dependent surface impedance
10.1121/10.0043069 · 2026 · External reference
Estimation of surface impedance at oblique incidence based on sparse array processing
10.1121/1.4983756 · 2017 · External reference
Angle-dependent sound absorption estimation using a compact microphone array
10.1121/10.0006566 · 2021 · External reference
Direct discrete complex image method for sound field evaluation above a non-locally reacting layer
10.1121/10.0007065 · 2021 · External reference
In situ measurements of the oblique incidence sound absorption coefficient for finite sized absorbers
10.1121/1.4938225 · 2016 · External reference
Sound field reconstruction using compressed separable projection-based equivalent source method
10.1142/s2591728523400030 · 2024 · External reference
Model-based Bayesian analysis in acoustics-a tutorial
10.1121/10.0001731 · 2020 · External reference
Spatial reconstruction of the sound field in a room in the modal frequency range using Bayesian inference
10.1121/10.0009040 · 2021 · External reference
Free-field characterization of locally reacting sound absorbers using Bayesian inference with sequential frequency transfer
10.1016/j.ymssp.2023.110780 · 2023 · External reference
A data-driven two-microphone method for in situ sound absorption measurements of porous materials
10.1121/10.0039101 · 2025 · External reference
Free-field method for inverse characterization of finite porous acoustic materials using feed forward neural networks
10.1121/10.0026239 · 2024 · External reference
Sound absorption estimation of finite porous samples with deep residual learning
10.1121/10.0021333 · 2023 · External reference
Analysis of the sound field above finite absorbers in the wave-number domain
10.1121/10.0010355 · 2022 · External reference
Nonlinear approach to approximate acoustic boundary admittance in cavities
10.1142/s0218396x07003214 · 2007 · External reference
Estimating the acoustical properties of locally reactive finite materials using the boundary element method
10.1121/10.0001393 · 2020 · External reference
Estimation of locally reacting surface impedance at modal frequencies using an eigenvalue approximation technique
10.1121/10.0006742 · 2021 · External reference
Bayesian approach for the in situ estimation of the acoustic boundary admittance
10.1142/s2591728523500135 · 2023 · External reference
Bayesian parameter identification in impedance boundary conditions for Helmholtz problems
10.1137/23m1591517 · 2024 · External reference
In situ estimation of the acoustic surface impedance using simulation-based inference
10.1121/10.0042242 · 2026 · External reference
Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
10.1016/j.jcp.2018.10.045 · 2019 · External reference
Physics-informed machine learning
10.1038/s42254-021-00314-5 · 2021 · External reference
Physics-informed neural networks for one-dimensional sound field predictions with parameterized sources and impedance boundaries
10.1121/10.0009057 · 2021 · External reference
Boundary integral neural networks for acoustic radiation prediction from noisy boundary data
10.1142/s2591728524400024 · 2025 · External reference
Room impulse response reconstruction with physics-informed deep learning
10.1121/10.0024750 · 2024 · External reference
Physics-informed neural networks for acoustic boundary admittance estimation
10.1016/j.ymssp.2024.111405 · 2024 · External reference
Neural impedance boundary (neib): A neural-network based framework for acoustic surface impedance estimation utilizing sparse measurement data
10.3397/in_2024_3955 · 2024 · External reference
Unresolved reference
External reference
Neural operator: Learning maps between function spaces with applications to PDEs
10.5555/3648699.3648788 · 2023 · External reference
Neural operators for accelerating scientific simulations and design
10.1038/s42254-024-00712-5 · 2024 · External reference
Sound propagation in realistic interactive 3D scenes with parameterized sources using deep neural operators
10.1073/pnas.2312159120 · 2024 · External reference
Modelling of superposition in 2D linear acoustic wave problems using Fourier neural operator networks
10.1051/aacus/2024078 · 2025 · External reference
Physics and geometry informed neural operator network with application to acoustic scattering
10.1016/j.ymssp.2025.113293 · 2025 · External reference
Physics-informed neural operators for predicting structural intensity from laser Doppler vibrometry measurements of plates
10.1016/j.ymssp.2026.114013 · 2026 · External reference
Applications of physics informed neural operators
10.1088/2632-2153/acd168 · 2023 · External reference
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
10.1038/s42256-021-00302-5 · 2021 · External reference
Universal approximation to nonlinear operators by neural networks with arbitrary activation functions and its application to dynamical systems
10.1109/72.392253 · 1995 · External reference
Unresolved reference
2024 · External reference
Learning the solution operator of parametric partial differential equations with physics-informed DeepONets
10.1126/sciadv.abi8605 · 2021 · External reference
Physics-informed neural operator for learning partial differential equations
10.48550/arxiv.2111.03794 · 2024 · External reference
Understanding and mitigating gradient flow pathologies in physics-informed neural networks
10.1137/20m1318043 · 2021 · External reference
Implicit neural representations with periodic activation functions
2020 · External reference
Decoupled weight decay regularization
2019 · External reference
Pytorch: An imperative style, high-performance deep learning library
2019 · External reference
