Pages that link to "Item:Q2117341"
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The following pages link to Exponential ReLU DNN expression of holomorphic maps in high dimension (Q2117341):
Displaying 30 items.
- Solving parametric partial differential equations with deep rectified quadratic unit neural networks (Q2103467) (← links)
- Structure probing neural network deflation (Q2124019) (← links)
- Deep solution operators for variational inequalities via proximal neural networks (Q2146915) (← links)
- ReLU deep neural networks from the hierarchical basis perspective (Q2159911) (← links)
- Variational physics informed neural networks: the role of quadratures and test functions (Q2162334) (← links)
- Deep ReLU network expression rates for option prices in high-dimensional, exponential Lévy models (Q2238770) (← links)
- Sparse approximation of triangular transports. I: The finite-dimensional case (Q2672289) (← links)
- Computation and learning in high dimensions. Abstracts from the workshop held August 1--7, 2021 (hybrid meeting) (Q2693017) (← links)
- Deep learning in high dimension: Neural network expression rates for generalized polynomial chaos expansions in UQ (Q4615657) (← links)
- Higher-Order Quasi-Monte Carlo Training of Deep Neural Networks (Q5015302) (← links)
- Physics Informed Neural Networks (PINNs) For Approximating Nonlinear Dispersive PDEs (Q5079535) (← links)
- Deep ReLU neural networks overcome the curse of dimensionality for partial integrodifferential equations (Q5873924) (← links)
- Neural network approximation (Q5887830) (← links)
- De Rham compatible deep neural network FEM (Q6057971) (← links)
- Deep ReLU neural network approximation in Bochner spaces and applications to parametric PDEs (Q6062166) (← links)
- Approximation theory of tree tensor networks: tensorized univariate functions (Q6076973) (← links)
- Approximation error for neural network operators by an averaged modulus of smoothness (Q6093307) (← links)
- Exponential ReLU neural network approximation rates for point and edge singularities (Q6101269) (← links)
- Exponential Convergence of Deep Operator Networks for Elliptic Partial Differential Equations (Q6108133) (← links)
- Deep Learning in High Dimension: Neural Network Expression Rates for Analytic Functions in \(\pmb{L^2(\mathbb{R}^d,\gamma_d)}\) (Q6109160) (← links)
- Deep Neural Networks with ReLU-Sine-Exponential Activations Break Curse of Dimensionality in Approximation on Hölder Class (Q6137593) (← links)
- Collocation approximation by deep neural ReLU networks for parametric and stochastic PDEs with lognormal inputs (Q6148127) (← links)
- Optimal approximation of infinite-dimensional holomorphic functions (Q6151536) (← links)
- Convergence rate of DeepONets for learning operators arising from advection-diffusion equations (Q6361196) (← links)
- Neural network expression rates and applications of the deep parametric PDE method in counterparty credit risk (Q6549602) (← links)
- Learning homogenization for elliptic operators (Q6583661) (← links)
- Deep ReLU networks and high-order finite element methods. II: Chebyšev emulation (Q6585367) (← links)
- Neural and spectral operator surrogates: unified construction and expression rate bounds (Q6601288) (← links)
- Parametric shape holomorphy of boundary integral operators with applications (Q6621317) (← links)
- Exploiting locality in sparse polynomial approximation of parametric elliptic PDEs and application to parameterized domains (Q6652068) (← links)
