A Structural Approach to the Design of Domain Specific Neural Network
  Architectures
This is a master's thesis concerning the theoretical ideas of geometric deep
learning. Geometric deep learning aims to provide a structured characterization
of neural network architectures, specifically focused on the ideas of
invariance and equivariance of data with respect to given transformations.
  This thesis aims to provide a theoretical evaluation of geometric deep
learning, compiling theoretical results that characterize the properties of
invariant neural networks with respect to learning performance.
Gerrit Nolte
# A Structural Approach to the Design of Domain Specific Neural Network Architectures

###### Abstract

We propose a structural approach to the design of Domain Specific Neural Network Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures Architectures Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures Architectures Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures Architectures Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures Architectures Architectures Architectures. The proposed approach is based on the use of a structural approach to the design of Domain Specific Neural Network Architectures