Results 111 to 120 of about 85,369,012 (181)

An Inexact Cayley Transform Method For Inverse Eigenvalue Problems [PDF]

, 2004
The Cayley transform method is a Newton-like method for solving inverse eigenvalue problems. If the problem is large, one can solve the Jacobian equation by iterative methods.
Raymond H. Chan, 白正简, Zheng-Jian Bai, Benedetta Morini   +3 more
core  

”New Connections between dynamical systems and Hamiltonian PDEs”

, 2010
This is a course of 8 hours on Hamiltonian PDEs: main examples, Nash-Moser IFT, tame estimates of the inverse linearzied operator, application to NLS and ...
BERTI, MASSIMILIANO
core  

Structural identifiability of constitutive relations from indirect field observations. [PDF]

PNAS Nexus
Ju YS.
europepmc   +1 more source

Learning variable-order time fractional diffusion equations using Physics-Informed Neural Networks. [PDF]

PLoS One
Ren L, Jin S.
europepmc   +1 more source

CoRoPINN: Cognitive region optimized physics-informed neural networks. [PDF]

PLoS One
Li J, Liao Y, Wang X, Deng J.
europepmc   +1 more source

Inverse problems in demography and biodemography [PDF]

Inverse problems play important role in science and engineering. Estimation of boundary conditions on the temperature distribution inside a metallurgical furnace, reconstruction of tissue density inside body on plane projections obtained with x-rays are ...
Anatoli I. Michalski
core  

Toward nonlinear representations with Gaussian-splat manifolds for physics-informed learning. [PDF]

Nat Commun
Han X, Chen K, Wang R, Wei G, Han L, Gao H.   +5 more
europepmc   +1 more source

Advances in computational biology approaches for digital modeling of tumor microenvironment. [PDF]

Brief Bioinform
Ming W, Lu H, Zeng T, Luo K, Xu J, Liu H.   +5 more
europepmc   +1 more source

Implementing physics-informed neural networks with deep learning for differential equations. [PDF]

Front Artif Intell
Emmert-Streib F, Tripathi S, Farea A, Holzinger A.   +3 more
europepmc   +1 more source

Convergence rates of general regularization methods for statistical inverse problems and applications [PDF]

During the past the convergence analysis for linear statistical inverse problems has mainly focused on spectral cut-off and Tikhonov type estimators. Spectral cut-off estimators achieve minimax rates for a broad range of smoothness classes and operators,
Bissantz, Nicolai, Ruymgaart, F., Munk, Axel, Hohage, T.   +3 more
core