Image classification, which is a fundamental element of Computer Vision (CV) and Artificial Intelligence (AI), has been researched intensively in numerous domains and embedded in …
Tensor networks (TNs) and neural networks (NNs) are two fundamental data modeling approaches. TNs were introduced to solve the curse of dimensionality in large-scale tensors …
Benchmarking of quantum machine learning (QML) algorithms is challenging due to the complexity and variability of QML systems, eg, regarding model ansatzes, data sets, training …
MA Khan, MN Aman, B Sikdar - IEEE Access, 2024 - ieeexplore.ieee.org
The existing body of research on quantum embedding techniques is not only confined in scope but also lacks a comprehensive understanding of the intricacies of the quantum …
H Chen, T Barthel - IEEE Transactions on Pattern Analysis and …, 2024 - ieeexplore.ieee.org
Tensor networks developed in the context of condensed matter physics try to approximate order-N tensors with a reduced number of degrees of freedom that is only polynomial in N …
T Stollenwerk, S Bhattacharya, M Cattelan… - KI-Künstliche …, 2024 - Springer
The goal of the project Q (AI) 2 was to acquire a broader basis of quantum computing enhanced AI and optimization algorithms for potential applications in the automotive …
XY Liu, Z Zhang - Proceedings of the 37th International Conference on …, 2023 - dl.acm.org
Google's" quantum supremacy" announcement [3] has received broad questions from academia and industry due to the debatable estimate of 10,000 years' running time for the …
Tensor networks are a popular and computationally efficient approach to simulate general quantum systems on classical computers and, in a broader sense, a framework for dealing …