Results 141 to 150 of about 21,388 (184)

Robust Physics-Informed Neural Network Approach for Estimating Heterogeneous Elastic Properties from Noisy Displacement Data. [PDF]

Adv Sci (Weinh)
Srikitrungruang T, Aghaee Dabaghan Fard S, Lemon M, Lee J, Zhou Y.   +4 more
europepmc   +1 more source

Neurosymbolic AI as an antithesis to scaling laws. [PDF]

PNAS Nexus
Velasquez A, Bhatt N, Topcu U, Wang Z, Sycara K, Stepputtis S, Neema S, Vallabha G.   +7 more
europepmc   +1 more source

Universal differential equations as a unifying modeling language for neuroscience. [PDF]

Front Comput Neurosci
El-Gazzar A, van Gerven M.
europepmc   +1 more source

A hybrid yang transform adomian decomposition method for solving time-fractional nonlinear partial differential equation. [PDF]

BMC Res Notes
Bekela AS, Deresse AT.
europepmc   +1 more source

Experimental and Numerical Characterization of Electrospun Piezoelectric Polyvinylidene Fluoride Nanocomposites Reinforced with Silver Nanoparticles. [PDF]

Materials (Basel)
Milenković S, Živić F, Grujović N, Virijević K, Bodić A, Petrović D.   +5 more
europepmc   +1 more source

Spectral shifted Chebyshev collocation technique with residual power series algorithm for time fractional problems. [PDF]

Sci Rep
Rida SZ, Arafa AAM, Hussein HS, Ameen IG, Mostafa MMM.   +4 more
europepmc   +1 more source

Dimensionless fluctuations balance applied to statistics and quantum physics. [PDF]

Sci Rep
Oliveira M, Valadares G, Rodrigues F, Freire M.   +3 more
europepmc   +1 more source

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Constrained Optimization with Low-Rank Tensors and Applications to Parametric Problems with PDEs

SIAM Journal of Scientific Computing, 2017
Sebastian Garreis, M. Ulbrich
semanticscholar   +3 more sources

Application of an Ultra Weak Variational Formulation of Elliptic PDEs to the Two-Dimensional Helmholtz Problem

SIAM Journal on Numerical Analysis, 1998
O. Cessenat, B. Després
semanticscholar   +3 more sources

VI-DGP: A Variational Inference Method with Deep Generative Prior for Solving High-Dimensional Inverse Problems

Journal of Scientific Computing, 2023
Solving high-dimensional Bayesian inverse problems (BIPs) with the variational inference (VI) method is promising but still challenging. The main difficulties arise from two aspects. First, VI methods approximate the posterior distribution using a simple
Yingzhi Xia, Qifeng Liao, Jinglai Li
semanticscholar   +1 more source