10 citations · 10 across the 2 of their papers we have counts for
8 papers · 1 filter
Towards a scalable discrete quantum generative adversarial neural network
Smit Chaudhary, Patrick Huembeli, Ian MacCormack +3
We introduce a fully quantum generative adversarial network intended for use with binary data. The architecture incorporates several features found in other classical and quantum m…
Entanglement Forging with generative neural network models
Patrick Huembeli, Giuseppe Carleo, Antonio Mezzacapo
The optimal use of quantum and classical computational techniques together is important to address problems that cannot be easily solved by quantum computations alone. This is the…
Avoiding local minima in Variational Quantum Algorithms with Neural Networks
Javier Rivera-Dean, Patrick Huembeli, Antonio Acín +1
Variational Quantum Algorithms have emerged as a leading paradigm for near-term quantum computation. In such algorithms, a parameterized quantum circuit is controlled via a classic…
Characterizing the loss landscape of variational quantum circuits
Patrick Huembeli, Alexandre Dauphin
Machine learning techniques enhanced by noisy intermediate-scale quantum (NISQ) devices and especially variational quantum circuits (VQC) have recently attracted much interest and…
Phase Detection with Neural Networks: Interpreting the Black Box
Anna Dawid, Patrick Huembeli, Michał Tomza +2
Neural networks (NNs) usually hinder any insight into the reasoning behind their predictions. We demonstrate how influence functions can unravel the black box of NN when trained to…
Unsupervised phase discovery with deep anomaly detection
Korbinian Kottmann, Patrick Huembeli, Maciej Lewenstein +1
We demonstrate how to explore phase diagrams with automated and unsupervised machine learning to find regions of interest for possible new phases. In contrast to supervised learnin…