5 papers
Variational Tensor Neural Networks for Deep Learning
Saeed S. Jahromi, Roman Orus
Deep neural networks (NNs) encounter scalability limitations when confronted with a vast array of neurons, thereby constraining their achievable network depth. To address this chal…
Kitaev honeycomb antiferromagnet in a field: quantum phase diagram for general spin
Saeed S. Jahromi, Max Hörmann, Patrick Adelhardt +4
We combine tensor-network approaches and high-order linked-cluster expansions to investigate the quantum phase diagram of the antiferromagnetic Kitaev's honeycomb model in a magnet…
Multi-disk clutch optimization using quantum annealing
John D. Malcolm, Alexander Roth, Mladjan Radic +5
In this work, we develop a new quantum algorithm to solve a combinatorial problem with significant practical relevance occurring in clutch manufacturing. It is demonstrated how qua…
Boosting Defect Detection in Manufacturing using Tensor Convolutional Neural Networks
Pablo Martin-Ramiro, Unai Sainz de la Maza, Sukhbinder Singh +2
Defect detection is one of the most important yet challenging tasks in the quality control stage in the manufacturing sector. In this work, we introduce a Tensor Convolutional Neur…
Improving Gradient Methods via Coordinate Transformations: Applications to Quantum Machine Learning
Pablo Bermejo, Borja Aizpurua, Roman Orus
Machine learning algorithms, both in their classical and quantum versions, heavily rely on optimization algorithms based on gradients, such as gradient descent and alike. The overa…