The following pages link to Philipp Petersen (Q281544):
Displaying 35 items.
- Shearlet approximation of functions with discontinuous derivatives (Q281545) (← links)
- Classification of edges using compactly supported shearlets (Q504380) (← links)
- Approximation properties of hybrid shearlet-wavelet frames for Sobolev spaces (Q2000536) (← links)
- Efficient approximation of solutions of parametric linear transport equations by ReLU DNNs (Q2026114) (← links)
- Topological properties of the set of functions generated by neural networks of fixed size (Q2031060) (← links)
- Numerical solution of the parametric diffusion equation by deep neural networks (Q2049099) (← links)
- A theoretical analysis of deep neural networks and parametric PDEs (Q2117329) (← links)
- Deep microlocal reconstruction for limited-angle tomography (Q2134111) (← links)
- The modern mathematics of deep learning (Q2164389) (← links)
- Anisotropic multiscale systems on bounded domains (Q2178832) (← links)
- Optimal approximation of piecewise smooth functions using deep ReLU neural networks (Q2182898) (← links)
- \(\Gamma\)-convergence of a shearlet-based Ginzburg-Landau energy (Q2197945) (← links)
- Linear independence of compactly supported separable shearlet systems (Q2347136) (← links)
- Regularization and numerical solution of the inverse scattering problem using shearlet frames (Q2397869) (← links)
- A recovery based linear finite element method for 1D bi-harmonic problems (Q2631057) (← links)
- Results on Non-linear Approximation for Wavelet Bases in Weighted Function Spaces (Q2814815) (← links)
- Progressive orthogonal wavelets: a review (Q2827615) (← links)
- Optimal Approximation with Sparsely Connected Deep Neural Networks (Q5025773) (← links)
- Extraction of Digital Wavefront Sets Using Applied Harmonic Analysis and Deep Neural Networks (Q5109278) (← links)
- Deep ReLU networks and high-order finite element methods (Q5132226) (← links)
- Error bounds for approximations with deep ReLU neural networks in Ws,p norms (Q5132228) (← links)
- Equivalence of approximation by convolutional neural networks and fully-connected networks (Q5218202) (← links)
- Deep neural networks can stably solve high-dimensional, noisy, non-linear inverse problems (Q5873926) (← links)
- The Modern Mathematics of Deep Learning (Q5879774) (← links)
- Exponential ReLU neural network approximation rates for point and edge singularities (Q6101269) (← links)
- Limitations of neural network training due to numerical instability of backpropagation (Q6122651) (← links)
- VC dimensions of group convolutional neural networks (Q6148443) (← links)
- Neural network approximation and estimation of classifiers with classification boundary in a Barron class (Q6165247) (← links)
- Topological properties of the set of functions generated by neural networks of fixed size (Q6303347) (← links)
- A Theoretical Analysis of Deep Neural Networks and Parametric PDEs (Q6316459) (← links)
- Deep Microlocal Reconstruction for Limited-Angle Tomography (Q6375076) (← links)
- Efficient Learning Using Spiking Neural Networks Equipped With Affine Encoders and Decoders (Q6529473) (← links)
- Large language models for mathematicians (Q6622601) (← links)
- First Order System Least Squares Neural Networks (Q6746669) (← links)
- High-dimensional classification problems with Barron regular boundaries under margin conditions (Q6757386) (← links)
