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Notation and Abbreviations

Math notation:

Symbol Meaning
$A$ matrix
$\eta$ learning rate or step size
$\Gamma$ boundary of computational domain $\Omega$
$f^{*}$ generic function to be approximated, typically unknown
$f$ approximate version of $f^{*}$
$\Omega$ computational domain
$\mathcal P^*$ continuous/ideal physical model
$\mathcal P$ discretized physical model, PDE
$\theta$ neural network params
$t$ time dimension
$\mathbf{u}$ vector-valued velocity
$x$ neural network input or spatial coordinate
$y$ neural network output
$y^*$ learning targets: ground truth, reference or observation data

Summary of the most important abbreviations:

Abbreviation Meaning
AI Mysterious buzzword popping up in all kinds of places these days
BNN Bayesian neural network
CNN Convolutional neural network (specific NN architecure)
DDPM Denoising diffusion probabilistic models (diffusion modeling variant)
DL Deep Learning
FM Flow matching (diffusion modeling variant)
FNO Fourier neural operator (specific NN architecure)
GD (steepest) Gradient Descent
MLP Multi-Layer Perceptron, a neural network with fully connected layers
NN Neural network (a generic one, in contrast to, e.g., a CNN or MLP)
PDE Partial Differential Equation
PBDL Physics-Based Deep Learning
SGD Stochastic Gradient Descent