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A curated list of recent textbooks, reviews, perspectives, and research papers related to quantum machine learning, variational quantum algorithms, tensor networks, and classical machine learning applications in quantum systems.
A repository for finishing my undergraduate thesis titled: Quantum Image Classifier Design with Data Re-uploading Quantum Convolution and Data Re-uploading Classifier Scheme.
DDQCL implementation using Qiskit. Variational quantum circuit that maps a randomly generated set of four 4-qubit input states to four 4-qubit output states. Circuit parameters are refined over time to get the lowest cost parameter set.
This project involves simulating a quantum classifier using a variational quantum circuit for binary classification problems. It is divided into three main parts, each contributing to the total project credits.
Noise-assisted Variational Quantum Thermalization (NAVQT) is an algorithm used to learn the parameters in a variational quantum circuit which prepares a thermal state of a Hamiltonian. Different from other approaches it considers the noise itself as a variational parameter which can be learned using approximations on the entropy.