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Why Capsule Neural Networks Do Not Scale: Challenging the Dynamic Parse-Tree Assumption
The capsule neural network (CapsNet), by Sabour, Frosst, and Hinton, is the first actual implementation of the conceptual idea of capsule neural networks.
A Simple and Efficient Tensor Calculus for Machine Learning
This leaves two options, to either change the underlying tensor representation in these frameworks or to develop a new, provably correct algorithm based on Einstein notation.
GENO -- GENeric Optimization for Classical Machine Learning
The framework is flexible enough to encompass most of the classical machine learning problems.
Computing Higher Order Derivatives of Matrix and Tensor Expressions
Optimization is an integral part of most machine learning systems and most numerical optimization schemes rely on the computation of derivatives.
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