Results 21 to 30 of about 116,861 (304)
Solving PDE-constrained Control Problems using Operator Learning [PDF]
AAAI Conference on Artificial Intelligence, 2021 The modeling and control of complex physical systems are essential in real-world problems. We propose a novel framework that is generally applicable to solving PDE-constrained optimal control problems by introducing surrogate models for PDE solution ...
Rakhoon Hwang +3 more
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Numerical Solution of the Advection-Diffusion Equation Using the Radial Basis Function
JTAM (Jurnal Teori dan Aplikasi Matematika), 2023 The advection-diffusion equation is a form of partial differential equation. This equation is also known as the transport equation. The purpose of this research is to approximatio the solution of advection-diffusion equation by numerical approach using ...
La Ode Sabran, Mohamad Syafi'i
doaj +1 more source
Viruses, 2020 Over 257 million individuals worldwide are chronically infected with the Hepatitis B Virus (HBV). Nucleos(t)ide analogues (NAs) are the first-line treatment option for most patients. Entecavir (ETV) and tenofovir disoproxil fumarate (TDF) are both potent,
Samuel Hall +3 more
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Revista Prática Docente, 2021 Nos anos 2000, no Paraná, pesquisas apontaram para a fragmentação nos cursos de formação continuada, o que contribuiu para a criação do Programa de Desenvolvimento Educacional (PDE). Nesse sentido, problematizamos os limites e as possibilidades do PDE na
Elaine Lazaroto +1 more
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Prostate sarcomas: A radiological mimic for benign prostatic hyperplasia
Urology Case Reports, 2020 Leimyosarcomas arising from the stroma of the prostate are very rare, accounting for 0.1% of malignancies. We describe a case that closely mimicked benign prostatic hypertrophy on magnetic resonance imaging.
Thomas Whish-Wilson +5 more
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Регуляторные исследования и экспертиза лекарственных средств, 2022 The manufacture of different medicinal products in shared facilities creates a risk of cross-contamination. One of the approaches to select the limits for possible contaminants is based on calculating the permitted daily exposure (PDE), i.e.
A. G. Solodovnikov +4 more
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PDE-Net 2.0: Learning PDEs from Data with A Numeric-Symbolic Hybrid Deep Network [PDF]
Journal of Computational Physics, 2018 Partial differential equations (PDEs) are commonly derived based on empirical observations. However, recent advances of technology enable us to collect and store massive amount of data, which offers new opportunities for data-driven discovery of PDEs. In
Zichao Long, Yiping Lu, Bin Dong
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PDE-constrained Models with Neural Network Terms: Optimization and Global Convergence [PDF]
Journal of Computational Physics, 2021 Recent research has used deep learning to develop partial differential equation (PDE) models in science and engineering. The functional form of the PDE is determined by a neural network, and the neural network parameters are calibrated to available data.
Justin A. Sirignano +2 more
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The Signature Kernel Is the Solution of a Goursat PDE [PDF]
SIAM Journal on Mathematics of Data Science, 2020 Recently, there has been an increased interest in the development of kernel methods for learning with sequential data. The signature kernel is a learning tool with potential to handle irregularly sampled, multivariate time series.
C. Salvi +4 more
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