Pages that link to "Item:Q911463"

The following pages link to On the limited memory BFGS method for large scale optimization (Q911463):

Displaying 50 items.

• A limited-memory BFGS-based differential evolution algorithm for optimal control of nonlinear systems with mixed control variables and probability constraints (Q6157441) (← links)
• Boundary-safe PINNs extension: application to non-linear parabolic PDEs in counterparty credit risk (Q6157931) (← links)
• Adaptive multigrid strategy for geometry optimization of large-scale three dimensional molecular mechanics (Q6158095) (← links)
• HiDeNN-FEM: a seamless machine learning approach to nonlinear finite element analysis (Q6159332) (← links)
• Deep learning soliton dynamics and complex potentials recognition for 1D and 2D \(\mathcal{PT}\)-symmetric saturable nonlinear Schrödinger equations (Q6160033) (← links)
• An efficient optimization algorithm that hybridizes DFTB and DFT theories both operated within the modified basin hopping method (Q6160297) (← links)
• Discovery of PDEs driven by data with sharp gradient or discontinuity (Q6161547) (← links)
• A local MM subspace method for solving constrained variational problems in image recovery (Q6162148) (← links)
• Iterated dynamic neighborhood search for packing equal circles on a sphere (Q6164321) (← links)
• Numerical analysis of the model of optimal savings and borrowing (Q6169119) (← links)
• A restart scheme for the memoryless BFGS method (Q6169212) (← links)
• Solution of the inverse problem of calculating a gas-liquid injector with a two-phase flow (Q6169883) (← links)
• Improved training of physics-informed neural networks for parabolic differential equations with sharply perturbed initial conditions (Q6171154) (← links)
• Automatic boundary fitting framework of boundary dependent physics-informed neural network solving partial differential equation with complex boundary conditions (Q6171169) (← links)
• A symmetry group based supervised learning method for solving partial differential equations (Q6171229) (← links)
• Probabilistic Registration for Gaussian Process Three-Dimensional Shape Modelling in the Presence of Extensive Missing Data (Q6171688) (← links)
• A priori error analysis of linear and nonlinear periodic Schrödinger equations with analytic potentials (Q6178633) (← links)
• Bayesian combinatorial multistudy factor analysis (Q6179124) (← links)
• Feature-adjacent multi-fidelity physics-informed machine learning for partial differential equations (Q6187659) (← links)
• Continuous Newton-like Methods Featuring Inertia and Variable Mass (Q6188502) (← links)
• On the global minimum of the classical potential energy for clusters bound by many-body forces (Q6189794) (← links)
• Hyperspectral super-resolution via low rank tensor triple decomposition (Q6189815) (← links)
• Gradient-enhanced physics-informed neural networks based on transfer learning for inverse problems of the variable coefficient differential equations (Q6191522) (← links)
• A log-Gaussian Cox process with sequential Monte Carlo for line narrowing in spectroscopy (Q6194412) (← links)
• Optimal Dirichlet boundary control by Fourier neural operators applied to nonlinear optics (Q6196628) (← links)
• Robust autoencoder feature selector for unsupervised feature selection (Q6198765) (← links)
• Many-stage optimal stabilized Runge-Kutta methods for hyperbolic partial differential equations (Q6200959) (← links)
• PDE-READ: human-readable partial differential equation discovery using deep learning (Q6488684) (← links)
• Certifying optimality of Bell inequality violations: noncommutative polynomial optimization through semidefinite programming and local optimization (Q6490315) (← links)
• Active learning for regression by inverse distance weighting (Q6496121) (← links)
• I-FENN with temporal convolutional networks: expediting the load-history analysis of non-local gradient damage propagation (Q6497179) (← links)
• Two-stage initial-value iterative physics-informed neural networks for simulating solitary waves of nonlinear wave equations (Q6497269) (← links)
• On quasi-Newton methods in fast Fourier transform-based micromechanics (Q6497745) (← links)
• Data-driven fusion and fission solutions in the Hirota-Satsuma-Ito equation via the physics-informed neural networks method (Q6497884) (← links)
• \texttt{Weak-PDE-LEARN}: a weak form based approach to discovering PDEs from noisy, limited data (Q6498485) (← links)
• An adaptive discrete physics-informed neural network method for solving the Cahn-Hilliard equation (Q6539904) (← links)
• Convergence analysis of block majorize-minimize subspace approach (Q6542454) (← links)
• Sparse signal reconstruction via Hager–Zhang-type schemes for constrained system of nonlinear equations (Q6548327) (← links)
• An efficient solution space exploring and descent method for packing equal spheres in a sphere (Q6551133) (← links)
• Identification of reaction rate parameters from uncertain spatially distributed concentration data using gradient-based PDE constrained optimization (Q6553613) (← links)
• Meshless physics-informed deep learning method for three-dimensional solid mechanics (Q6554056) (← links)
• \(PT\)-symmetric PINN for integrable nonlocal equations: forward and inverse problems (Q6554430) (← links)
• Adaptive sampling physics-informed neural network method for high-order rogue waves and parameters discovery of the \((2+1)\)-dimensional CHKP equation (Q6554449) (← links)
• A probabilistic framework for multidisciplinary design: application to the hydrostructural optimization of supercavitating hydrofoils (Q6555245) (← links)
• A structured L-BFGS method and its application to inverse problems (Q6557640) (← links)
• On the convergence of inexact alternate minimization in problems with \(\ell_0\) penalties (Q6559515) (← links)
• An optimized CIP-FEM to reduce the pollution errors for the Helmholtz equation on a general unstructured mesh (Q6560695) (← links)
• Learning particle swarming models from data with Gaussian processes (Q6562843) (← links)
• Data driven soliton solution of the nonlinear Schrödinger equation with certain \(\mathcal{PT}\)-symmetric potentials via deep learning (Q6563626) (← links)
• The appeals of quadratic majorization-minimization (Q6568947) (← links)