|
capital gain tax |
3 |
|
fuzzy sets |
3 |
|
gps trajectory data segmentation |
3 |
|
newton's method |
3 |
|
numerical integral simulation |
3 |
|
particle swarm optimization |
3 |
|
probabilistic logic |
3 |
|
regime switching |
3 |
|
uncertainty quantification (uq) |
3 |
|
65c35 |
2 |
|
68w20 |
2 |
|
90c08 |
2 |
|
90c25 |
2 |
|
bayesian inversion |
2 |
|
convergence analysis |
2 |
|
convex optimization |
2 |
|
deep particle method |
2 |
|
dynamic programming (dp) principle |
2 |
|
dynamically low-dimensional approximation |
2 |
|
generalized multiscale finite element method (gmsfem) |
2 |
|
hamilton-jacobi-bellman (hjb) equation |
2 |
|
high-contrast problem |
2 |
|
immersed interface method |
2 |
|
limit order book (lob) |
2 |
|
market impact |
2 |
|
moving contact lines |
2 |
|
multiscale potential |
2 |
|
multiscale reduced basis |
2 |
|
online adaptive method |
2 |
|
optimal transport |
2 |
|
parametric finite element method |
2 |
|
proper orthogonal decomposition |
2 |
|
proper orthogonal decomposition (pod) |
2 |
|
proper orthogonal decomposition (pod) method |
2 |
|
quadratic programming (qp) |
2 |
|
random block coordinate descent |
2 |
|
random partial differential equations (rpdes) |
2 |
|
regime-switching |
2 |
|
schrödinger equation |
2 |
|
stochastic partial differential equations (spdes) |
2 |
|
uncertainty quantification |
2 |
|
value iteration method |
2 |
|
adaptivity algorithm |
1 |
|
analysis of variance |
1 |
|
anderson localization |
1 |
|
artificial boundary condition |
1 |
|
artificial boundary condition (abc) |
1 |
|
artificial discontinuity |
1 |
|
asymptotic analysis |
1 |
|
asymptotic method |
1 |
|
backward error analysis |
1 |
|
bayesian elliptic inverse problems |
1 |
|
bayesian inverse problems |
1 |
|
bi-orthogonality |
1 |
|
cellular locomotion |
1 |
|
chaotic |
1 |
|
chemotaxis |
1 |
|
clustering algorithm |
1 |
|
composite maps |
1 |
|
computational cardiology |
1 |
|
conical crossings |
1 |
|
contact angle hysteresis |
1 |
|
cordes condition |
1 |
|
critical mass |
1 |
|
data-driven methods |
1 |
|
data-driven model reduction method |
1 |
|
deep learning |
1 |
|
deep neural networks |
1 |
|
diffusion enhancement |
1 |
|
diffusion equation |
1 |
|
direct sampling method |
1 |
|
discontinuous extreme learning machine |
1 |
|
discrete artificial boundary condition (dabc) |
1 |
|
duncan- mortensen-zakai equation |
1 |
|
dynamic mode decomposition |
1 |
|
effective diffusivity |
1 |
|
eigenfunction expansion |
1 |
|
elliptic |
1 |
|
elliptic inverse problems |
1 |
|
energy method |
1 |
|
enriched multiscale basis |
1 |
|
ensemble filtering methods |
1 |
|
equations |
1 |
|
exciton diffusion |
1 |
|
exciton diffusion length |
1 |
|
fast algorithm |
1 |
|
feynman-kac semigroups |
1 |
|
finite element methods |
1 |
|
finite-time blowup |
1 |
|
fitz-hugh nagumo model |
1 |
|
fokker-planck-kolmogorov equation |
1 |
|
free boundary problems |
1 |
|
fully parabolic keller-segel system |
1 |
|
generalized polynomial chaos |
1 |
|
greedy algorithm |
1 |
|
hamiltonian dynamical system |
1 |
|
hamiltonian monte carlo (hmc) method |
1 |
|
high resolution scheme |
1 |
|
high-contrast |
1 |
|
high-contrast ratio |
1 |
|
hodgkin-huxley model |
1 |
|
homogenization |
1 |
|
interacting particle approximation |
1 |
|
interacting particle method |
1 |
|
interacting particle-field approximation |
1 |
|
interface condition |
1 |
|
interface problem |
1 |
|
interface problems |
1 |
|
inverse source problem |
1 |
|
karhunen-loeve expansion |
1 |
|
karhunen-loè |
1 |
|
karhunen–loève expansion |
1 |
|
keller–segel system |
1 |
|
keratocytes |
1 |
|
kpp front speeds |
1 |
|
landau-zener formula |
1 |
|
level set method |
1 |
|
limited aperture data |
1 |
|
linear elasticity |
1 |
|
liouville equation |
1 |
|
localized basis function |
1 |
|
localized data-driven stochastic basis |
1 |
|
localized orthogonal decomposition |
1 |
|
low-dimensional structure |
1 |
|
maximum principle |
1 |
|
mechanosensing |
1 |
|
mesh-free method |
1 |
|
model reduction |
1 |
|
multilevel monte carlo (mlmc) |
1 |
|
multiple scales |
1 |
|
multiple time scales |
1 |
|
multiscale basis functions |
1 |
|
multiscale elliptic pdes |
1 |
|
multiscale elliptic pdes with random coefficients |
1 |
|
multiscale finite element method |
1 |
|
multiscale finite element method (msfem) |
1 |
|
multiscale problems |
1 |
|
multiscale reduced basis function |
1 |
|
neural network |
1 |
|
nonlinear filtering problems |
1 |
|
nonlinear klein-gordon equation (nklge) |
1 |
|
normalizing flows |
1 |
|
operator compression |
1 |
|
operator splitting method |
1 |
|
optimal regularization parameter |
1 |
|
optimal transportation |
1 |
|
optimization method |
1 |
|
organic semiconductor |
1 |
|
parabolic inverse source problems |
1 |
|
physics-informed neural networks |
1 |
|
pressure poisson equation |
1 |
|
quasi-monte carlo method |
1 |
|
quasi-monte carlo sampling |
1 |
|
random domain |
1 |
|
random flows |
1 |
|
random schrödinger equation |
1 |
|
real-time algorithm |
1 |
|
reduced basis |
1 |
|
reduced-order model |
1 |
|
reduced-order models |
1 |
|
regularization method |
1 |
|
rough coefficients |
1 |
|
semiclassical regime |
1 |
|
semiclassical schrödinger equation |
1 |
|
separability |
1 |
|
sine-gordon equation |
1 |
|
singularity detection |
1 |
|
soliton |
1 |
|
sparsity |
1 |
|
split local absorbing boundary |
1 |
|
stiff equations |
1 |
|
stochastic error estimate |
1 |
|
stochastic flow |
1 |
|
stochastic flows |
1 |
|
stochastic nonlinear pdes |
1 |
|
stochastic partial differential equations |
1 |
|
surface hopping method |
1 |
|
tailored finite point method (tfpm) |
1 |
|
the green's function |
1 |
|
time-dependent potential |
1 |
|
topological changes |
1 |
|
two-parameter expansion |
1 |
|
unbounded domain |
1 |
|
uncertainty qualification |
1 |
|
variational inference |
1 |
|
variational problems |
1 |
|
ve expansion |
1 |
|
wasserstein distance |
1 |
|
weighted and interpolated nearest-neighbors |
1 |
