Firstly, I will enlighten how different quantum information is compared to classical information and how this can affect machine learning algorithms. Then I discuss different attempts to obtain quantum neural networks and their performances. In the last part I will focus on applications of machine learning to problems in quantum physics and medicine.
One of the possible applications of quantum computers in the near future are simulations of physics. An example are quantum gravitational systems associated with the Planck scale physics. Such systems are expected to be of the many-body type, which justifies utility of quantum computations in the analysis of their complex quantum behaviour. In this talk, loop quantum gravity - a leading...
Support vector machines (SVMs) are a well-established classifier effectively deployed in an array of pattern recognition and classification tasks. In this work, we consider extending classic SVMs with quantum kernels and applying them to satellite data analysis.
The design and implementation of SVMs with quantum kernels (hybrid SVMs) is presented. It consists of the Quantum Kernel Estimation...
