Pages that link to "Item:Q2197226"

The following pages link to Deep neural network approach to forward-inverse problems (Q2197226):

Displaying 20 items.

• Traveling wave solutions of partial differential equations via neural networks (Q1983171) (← links)
• Regularization by architecture: a deep prior approach for inverse problems (Q1988362) (← links)
• Neural network approach to data-driven estimation of chemotactic sensitivity in the Keller-Segel model (Q2092227) (← links)
• Trend to equilibrium for the kinetic Fokker-Planck equation via the neural network approach (Q2125428) (← links)
• Solving the linear transport equation by a deep neural network approach (Q2129138) (← links)
• Lagrangian dual framework for conservative neural network solutions of kinetic equations (Q2158858) (← links)
• Transfer learning based physics-informed neural networks for solving inverse problems in engineering structures under different loading scenarios (Q2683433) (← links)
• Data-driven forward-inverse problems for Yajima-Oikawa system using deep learning with parameter regularization (Q2684140) (← links)
• Data-consistent neural networks for solving nonlinear inverse problems (Q2697358) (← links)
• (Q4581062) (← links)
• Neural networks for FDTD‐backed permittivity reconstruction (Q4672416) (← links)
• (Q4984356) (← links)
• Construct Deep Neural Networks based on Direct Sampling Methods for Solving Electrical Impedance Tomography (Q4997381) (← links)
• Discretization of parameter identification in PDEs using neural networks (Q5058109) (← links)
• Convolutional Neural Networks in Phase Space and Inverse Problems (Q5149211) (← links)
• Deep synthesis network for regularizing inverse problems (Q5150821) (← links)
• The model reduction of the Vlasov–Poisson–Fokker–Planck system to the Poisson–Nernst–Planck system <i>via</i> the Deep Neural Network Approach (Q5163496) (← links)
• Laplace based Bayesian inference for ordinary differential equation models using regularized artificial neural networks (Q6063150) (← links)
• The deep minimizing movement scheme (Q6087937) (← links)
• Scaling Up Bayesian Uncertainty Quantification for Inverse Problems Using Deep Neural Networks (Q6109143) (← links)