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Numerical Approximation of Partial Differential Equations by a Variable Projection Method with Artificial Neural Networks
For linear PDEs, enforcing the boundary/initial value problem on the collocation points leads to a separable nonlinear least squares problem about the network coefficients.
On Computing the Hyperparameter of Extreme Learning Machines: Algorithm and Application to Computational PDEs, and Comparison with Classical and High-Order Finite Elements
We consider the use of extreme learning machines (ELM) for computational partial differential equations (PDE).
Protecting Big Data Privacy Using Randomized Tensor Network Decomposition and Dispersed Tensor Computation
The distributed tensor representations are dispersed on multiple clouds / fogs or servers / devices with metadata privacy, this provides both distributed trust and management to seamlessly secure big data storage, communication, sharing, and computation.
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