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Found 7 papers, 0 papers with code
Anisotropic Diffusion Stencils: From Simple Derivations over Stability Estimates to ResNet Implementations
Our directional splitting also allows a very natural translation of the explicit scheme into ResNet blocks.
Efficient Neural Generation of 4K Masks for Homogeneous Diffusion Inpainting
It trains a mask generation network with the help of a neural inpainting surrogate.
Deep Spatial and Tonal Data Optimisation for Homogeneous Diffusion Inpainting
This provides real-time performance with high quality results.
CNN-based Euler's Elastica Inpainting with Deep Energy and Deep Image Prior
As a remedy, we design the first neural algorithm that simulates inpainting with Euler's Elastica.
Designing Rotationally Invariant Neural Networks from PDEs and Variational Methods
With only a few small filters, they can achieve the same invariance as existing techniques which require a fine-grained sampling of orientations.
Connections between Numerical Algorithms for PDEs and Neural Networks
We connect these concepts to residual networks, recurrent neural networks, and U-net architectures.
Translating Numerical Concepts for PDEs into Neural Architectures
We investigate what can be learned from translating numerical algorithms into neural networks.
