On the sample complexity of quantum Boltzmann machine learning
Abstract Quantum Boltzmann machines (QBMs) are machine-learning models for both
classical and quantum data. We give an operational definition of QBM learning in terms of …
classical and quantum data. We give an operational definition of QBM learning in terms of …
Benchmarking quantum generative learning: A study on scalability and noise resilience using QUARK
Quantum computing promises a disruptive impact on machine learning algorithms, taking
advantage of the exponentially large Hilbert space available. However, it is not clear how to …
advantage of the exponentially large Hilbert space available. However, it is not clear how to …
Shadow-Frugal Expectation-Value-Sampling Variational Quantum Generative Model
K Shen, A Kurkin, AP Salinas, E Shishenina… - arxiv preprint arxiv …, 2024 - arxiv.org
Expectation Value Samplers (EVSs) are quantum-computer-based generative models that
can learn high-dimensional continuous distributions by measuring the expectation values of …
can learn high-dimensional continuous distributions by measuring the expectation values of …
Quantum Computing for Automotive Applications: From Algorithms to Applications
Quantum computing could impact various industries, with the automotive industry with many
computational challenges, from optimizing supply chains and manufacturing to vehicle …
computational challenges, from optimizing supply chains and manufacturing to vehicle …
Pilot-Quantum: A Quantum-HPC Middleware for Resource, Workload and Task Management
As quantum hardware continues to scale, managing the heterogeneity of resources and
applications--spanning diverse quantum and classical hardware and software frameworks …
applications--spanning diverse quantum and classical hardware and software frameworks …
[PDF][PDF] Quantum Computing for Automotive Applications: From Algorithms to Applications
LH Kiwit, M Erdmann, L Müller, C Kumar, YA Berrada… - researchgate.net
Quantum computing could impact various industries, with the automotive industry with many
computational challenges, from optimizing supply chains and manufacturing to vehicle …
computational challenges, from optimizing supply chains and manufacturing to vehicle …