Results 251 to 260 of about 116,861 (304)
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Continuous PDE Dynamics Forecasting with Implicit Neural Representations
International Conference on Learning Representations, 2022Effective data-driven PDE forecasting methods often rely on fixed spatial and / or temporal discretizations. This raises limitations in real-world applications like weather prediction where flexible extrapolation at arbitrary spatiotemporal locations is ...
Yuan Yin +4 more
semanticscholar +1 more source
Blending neural operators and relaxation methods in PDE numerical solvers
Nature Machine Intelligence, 2022Neural networks suffer from spectral bias and have difficulty representing the high-frequency components of a function, whereas relaxation methods can resolve high frequencies efficiently but stall at moderate to low frequencies.
Enrui Zhang +5 more
semanticscholar +1 more source
Phosphodiesterases (PDEs) and PDE inhibitors for treatment of LUTS
Neurourology and Urodynamics, 2007Lower urinary tract (LUT) smooth muscle can be relaxed by drugs that increase intracellular concentrations of cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP). Both of these substances are degraded by phosphodiesterases (PDEs), which play a central role in the regulation of smooth muscle tone.
Karl-Erik, Andersson +3 more
openaire +2 more sources
2018
This chapter of the book is devoted to the study of parabolic–parabolic PDE loops by means of the small-gain methodology. The results contained in the present chapter allow the existence of non-local reaction terms (both distributed terms and boundary terms) as well as distributed and boundary inputs.
Iasson Karafyllis, Miroslav Krstic
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This chapter of the book is devoted to the study of parabolic–parabolic PDE loops by means of the small-gain methodology. The results contained in the present chapter allow the existence of non-local reaction terms (both distributed terms and boundary terms) as well as distributed and boundary inputs.
Iasson Karafyllis, Miroslav Krstic
openaire +1 more source
Asymptotic Methods in Nonlinear Wave Phenomena, 2007
Within the context of the inverse Lie problem the question whether there exist PDEs that are characterized by their Lie point symmetries may be addressed. In a recent paper the authors called these equations Lie remarkable. In this paper we exhibit various examples of Lie remarkable equations, including some multidimensional Monge-Ampere type equations.
G. MANNO, OLIVERI, Francesco, R. VITOLO
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Within the context of the inverse Lie problem the question whether there exist PDEs that are characterized by their Lie point symmetries may be addressed. In a recent paper the authors called these equations Lie remarkable. In this paper we exhibit various examples of Lie remarkable equations, including some multidimensional Monge-Ampere type equations.
G. MANNO, OLIVERI, Francesco, R. VITOLO
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(CO)Bordisms in PDEs and quantum PDEs
Reports on Mathematical Physics, 1996zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training
International Conference on Machine LearningPre-training has been investigated to improve the efficiency and performance of training neural operators in data-scarce settings. However, it is largely in its infancy due to the inherent complexity and diversity, such as long trajectories, multiple ...
Zhongkai Hao +8 more
semanticscholar +1 more source
2018
The chapter is devoted to the development of the small-gain methodology for coupled 1-D, hyperbolic, first-order PDEs under the presence of external inputs. Our aim is the derivation of sufficient conditions that guarantee ISS for a given system of coupled hyperbolic PDEs. Globally, Lipschitz nonlinear, non-local terms are allowed to be present both in
Iasson Karafyllis, Miroslav Krstic
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The chapter is devoted to the development of the small-gain methodology for coupled 1-D, hyperbolic, first-order PDEs under the presence of external inputs. Our aim is the derivation of sufficient conditions that guarantee ISS for a given system of coupled hyperbolic PDEs. Globally, Lipschitz nonlinear, non-local terms are allowed to be present both in
Iasson Karafyllis, Miroslav Krstic
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DiffusionPDE: Generative PDE-Solving Under Partial Observation
Neural Information Processing SystemsWe introduce a general framework for solving partial differential equations (PDEs) using generative diffusion models. In particular, we focus on the scenarios where we do not have the full knowledge of the scene necessary to apply classical solvers. Most
Jiahe Huang +3 more
semanticscholar +1 more source
Annual Reviews in Control, 2007
Abstract This paper presents several recently developed techniques for adaptive control of PDE systems. Three different design methods are employed—the Lyapunov design, the passivity-based design, and the swapping design. The basic ideas for each design are introduced through benchmark plants with constant unknown coefficients.
Miroslav Krstic, Andrey Smyshlyaev
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Abstract This paper presents several recently developed techniques for adaptive control of PDE systems. Three different design methods are employed—the Lyapunov design, the passivity-based design, and the swapping design. The basic ideas for each design are introduced through benchmark plants with constant unknown coefficients.
Miroslav Krstic, Andrey Smyshlyaev
openaire +1 more source