Results 21 to 30 of about 82,072,160 (134)
Complexity of Linear Ill-Posed Problems in Hilbert Space
, 2017 Information complexity of ill-posed problems may be seen as controversial. On the one hand side there were pessimistic results stating that the complexity is infinite, while on the other hand side the theory of ill-posed problems is well developed.
Mathé, Peter, Pereverzev, Sergei V.
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Differentiable Randers‐Finsler Eikonal Solvers
Computer Graphics Forum, EarlyView.Abstract Fast and differentiable solvers for anisotropic and asymmetric distance fields are a key primitive in geometry processing, enabling gradient‐based optimization over metrics, drift fields, and downstream objectives that depend on geodesic distances and geodesics.
Barak Gahtan +2 more
wiley +1 more source
Least squares methods for partial differential equations:Ill-conditioned and ill-posed problems [PDF]
This thesis explores the theoretical foundations of least squares methods for the numerical solution of PDEs, and provides new methods for ill-conditioned and ill-posed problems.
Monsuur, H.
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Reinforcement Learning for Jump‐Diffusions, With Financial Applications
Mathematical Finance, EarlyView.ABSTRACT We study continuous‐time reinforcement learning (RL) for stochastic control in which system dynamics are governed by jump‐diffusion processes. We formulate an entropy‐regularized exploratory control problem with stochastic policies to capture the exploration–exploitation balance essential for RL.
Xuefeng Gao, Lingfei Li, Xun Yu Zhou
wiley +1 more source
Comparing parameter choice methods for regularization of ill-posed problems [PDF]
, 2011 In the literature on regularization, many different parameter choice methods have been proposed in both deterministic and stochastic settings. However, based on the available information, it is not always easy to know how well a particular method will ...
Bauer, F., Lukas, M.A.
core
Mathematical Finance, EarlyView.ABSTRACT We extend the notion of forward performance criteria to settings with random endowment in incomplete markets. Building on these results, we introduce and develop the novel concept of forward optimized certainty equivalent (forward OCE), which offers a genuinely dynamic valuation mechanism that accommodates progressively adaptive market model ...
Gechun Liang +2 more
wiley +1 more source
Applied Research, Volume 5, Issue 5, October 2026.UniNS is a hybrid neuro‐symbolic framework that simulates nanoscale swarms in tumor microenvironments by coupling mesoscopic hydrodynamics with structure‐regularized causal discovery. It reduces biochemical prediction errors by 27.3% and dynamically prevents spurious correlations, offering a scalable, thermodynamically consistent testbed for precision ...
Xinyuan Chen +3 more
wiley +1 more source
, 2017 We study Tikhonov regularization for ill-posed non-linear operator equations in Hilbert scales. Our focus is on the interplay between the smoothness-promoting properties of the penalty and the smoothness inherent in the solution.
Mathé, Peter +3 more
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Applied Research, Volume 5, Issue 5, October 2026.This study introduces a structurally cascaded physics‐informed graph neural network to model tumor microenvironments accurately. By enforcing a directional dependency from mechanical strain to biochemical secretion, the method eliminates unphysical artifacts and significantly improves predictive accuracy for precision healthcare applications.
Xinyuan Chen +2 more
wiley +1 more source
Subspace Acceleration for Efficient Nonlinear Water Wave Simulation
International Journal for Numerical Methods in Fluids, Volume 98, Issue 10, Page 1165-1180, October 2026.We introduce an exponentially weighted subspace acceleration technique to reduce GMRES iterations for solving the Poisson equation with time‐dependent coefficients in nonlinear, dispersive free‐surface flows governed by the incompressible Navier‐Stokes equations. The method significantly reduces memory requirements and computational complexity compared
Rasmus Kleist Hørlyck Sørensen +3 more
wiley +1 more source