TensorFlow Quantum: A Software Framework for Quantum Machine Learning. - Michael Broughton; Guillaume Verdon; Trevor McCourt; Antonio J. Martinez; Jae Hyeon Yoo; Sergei V. Isakov; Philip Massey; Murphy Yuezhen Niu; Ramin Halavati; Evan Peters; Martin Leib; Andrea Skolik; et al. (CoRR, 2020)

Layerwise learning for quantum neural networks. - Andrea Skolik; Jarrod R. McClean; Masoud Mohseni; Patrick van der Smagt; Martin Leib (Quantum Mach. Intell., 2021)

Hyperparameter optimization of hybrid quantum neural networks for car classification. - Asel Sagingalieva; Andrii Kurkin; Artem Melnikov; Daniil Kuhmistrov; Michael Perelshtein; Alexey Melnikov 003; Andrea Skolik; David Von Dollen (CoRR, 2022)

Equivariant quantum circuits for learning on weighted graphs. - Andrea Skolik; Michele Cattelan; Sheir Yarkoni; Thomas Bäck; Vedran Dunjko (CoRR, 2022)

Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning. - Andrea Skolik; Sofiène Jerbi; Vedran Dunjko (Quantum, 2022)

Hybrid quantum ResNet for car classification and its hyperparameter optimization. - Asel Sagingalieva; Mohammad Kordzanganeh; Andrii Kurkin; Artem Melnikov; Daniil Kuhmistrov; Michael Perelshtein; Alexey Melnikov 003; Andrea Skolik; David Von Dollen (Quantum Mach. Intell., 2023)

$ mathrm{Q(AI)}^2$: Quantum Artificial Intelligence for the Automotive Industry. - Tobias Stollenwerk; Somtapa Bhattacharya; Michele Cattelan; Alessandro Ciani; Gabriele Compostella; David Headley; Johannes Klepsch; Matthias Klusch; Markus Leder; Antonio Macaluso; Kristel Michielsen; Dmytro Nabok; et al. (Künstliche Intell., 2024)