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Found 6 papers, 2 papers with code
Higher-order topological kernels via quantum computation
Topological data analysis (TDA) has emerged as a powerful tool for extracting meaningful insights from complex data.
The Quantum Path Kernel: a Generalized Quantum Neural Tangent Kernel for Deep Quantum Machine Learning
A key issue is how to address the inherent non-linearity of classical deep learning, a problem in the quantum domain due to the fact that the composition of an arbitrary number of quantum gates, consisting of a series of sequential unitary transformations, is intrinsically linear.
Automatic and effective discovery of quantum kernels
Quantum computing can empower machine learning models by enabling kernel machines to leverage quantum kernels for representing similarity measures between data.
Quantum Advantage Seeker with Kernels (QuASK): a software framework to speed up the research in quantum machine learning
Our framework can also be used as a library and integrated into pre-existing software, maximizing code reuse.
Computing Graph Edit Distance with Algorithms on Quantum Devices
Distance measures provide the foundation for many popular algorithms in Machine Learning and Pattern Recognition.
Facial Expression Recognition on a Quantum Computer
We address the problem of facial expression recognition and show a possible solution using a quantum machine learning approach.
