Continual learning in medical image analysis: A survey
In the dynamic realm of practical clinical scenarios, Continual Learning (CL) has gained
increasing interest in medical image analysis due to its potential to address major …
increasing interest in medical image analysis due to its potential to address major …
A quantum “black box” for entropy calculation
A significant part of global quantum computing research has been conducted based on
quantum mechanics, which can now be used with quantum computers. However, designing …
quantum mechanics, which can now be used with quantum computers. However, designing …
The role of data embedding in equivariant quantum convolutional neural networks
Geometric deep learning refers to the scenario in which the symmetries of a dataset are
used to constrain the parameter space of a neural network and thus, improve their …
used to constrain the parameter space of a neural network and thus, improve their …
Deep Q-learning with hybrid quantum neural network on solving maze problems
Quantum computing holds great potential for advancing the limitations of machine learning
algorithms to handle higher dimensions of data and reduce overall training parameters in …
algorithms to handle higher dimensions of data and reduce overall training parameters in …
A parameterized quantum circuit for estimating distribution measures
Quantum computing is a new and exciting field with the potential to solve some of the world's
most challenging problems. Currently, with the rise of quantum computers, the main …
most challenging problems. Currently, with the rise of quantum computers, the main …
A quantum procedure for estimating information gain in Boolean classification task
A substantial portion of global quantum computing research has been conducted using
quantum mechanics, which recently has been applied to quantum computers. However, the …
quantum mechanics, which recently has been applied to quantum computers. However, the …