An quantum algorithm for feedforward neural networks tested on existing quantum hardware. - Daniele Bajoni; Dario Gerace; Chiara Macchiavello; Francesco Tacchino; Panagiotis Kl. Barkoutsos; Ivano Tavernelli (ESANN, 2020)

Variational learning for quantum artificial neural networks. - Francesco Tacchino; Panagiotis Kl. Barkoutsos; Chiara Macchiavello; Dario Gerace; Ivano Tavernelli; Daniele Bajoni (QCE, 2020)

Quantum computing model of an artificial neuron with continuously valued input data. - Stefano Mangini; Francesco Tacchino; Dario Gerace; Chiara Macchiavello; Daniele Bajoni (Mach. Learn. Sci. Technol., 2020)

Representation Learning via Quantum Neural Tangent Kernels. - Junyu Liu; Francesco Tacchino; Jennifer R. Glick; Liang Jiang; Antonio Mezzacapo (CoRR, 2021)

Algorithmic Error Mitigation Scheme for Current Quantum Processors. - Philippe Suchsland; Francesco Tacchino; Mark H. Fischer; Titus Neupert; Panagiotis Kl. Barkoutsos; Ivano Tavernelli (Quantum, 2021)

An analytic theory for the dynamics of wide quantum neural networks. - Junyu Liu; Khadijeh Najafi; Kunal Sharma; Francesco Tacchino; Liang Jiang; Antonio Mezzacapo (CoRR, 2022)

Quantum neural networks force fields generation. - Oriel Kiss; Francesco Tacchino; Sofia Vallecorsa; Ivano Tavernelli (Mach. Learn. Sci. Technol., 2022)

Quantum Generative Adversarial Networks For Anomaly Detection In High Energy Physics. - Elie Bermot; Christa Zoufal; Michele Grossi; Julian Schuhmacher; Francesco Tacchino; Sofia Vallecorsa; Ivano Tavernelli (QCE, 2023)

Quadratic quantum speedup in evaluating bilinear risk functions. - Gabriele Agliardi; Corey O'Meara; Kavitha Yogaraj; Kumar Jang Bahadur Ghosh; Piergiacomo Sabino; Marina Fernández-Campoamor; Giorgio Cortiana; Juan Bernabé-Moreno; Francesco Tacchino; Antonio Mezzacapo; Omar Shehab (CoRR, 2023)

Symmetry-invariant quantum machine learning force fields. - Isabel Nha Minh Le; Oriel Kiss; Julian Schuhmacher; Ivano Tavernelli; Francesco Tacchino (CoRR, 2023)

Quantum algorithms for quantum dynamics. - Alexander Miessen; Pauline J. Ollitrault; Francesco Tacchino; Ivano Tavernelli (Nat. Comput. Sci., 2023)

Quantum machine learning framework for virtual screening in drug discovery: a prospective quantum advantage. - Stefano Mensa; Mustafa Emre Sahin; Francesco Tacchino; Panagiotis Kl. Barkoutsos; Ivano Tavernelli (Mach. Learn. Sci. Technol., 2023)

Optimizing Quantum Classification Algorithms on Classical Benchmark Datasets. - Manuel John; Julian Schuhmacher; Panagiotis Kl. Barkoutsos; Ivano Tavernelli; Francesco Tacchino (Entropy, 2023)

On Hitting Times for General Quantum Markov Processes. - Lorenzo Laneve; Francesco Tacchino; Ivano Tavernelli (Quantum, 2023)

Pulse-efficient quantum machine learning. - André Melo; Nathan Earnest-Noble; Francesco Tacchino (Quantum, 2023)

Quantum algorithms for grid-based variational time evolution. - Pauline J. Ollitrault; Sven Jandura; Alexander Miessen; Irene Burghardt; Rocco Martinazzo; Francesco Tacchino; Ivano Tavernelli (Quantum, 2023)

Unravelling physics beyond the standard model with classical and quantum anomaly detection. - Julian Schuhmacher; Laura Boggia; Vasilis Belis; Ema Puljak; Michele Grossi; Maurizio Pierini; Sofia Vallecorsa; Francesco Tacchino; Panagiotis Kl. Barkoutsos; Ivano Tavernelli (Mach. Learn. Sci. Technol., 2023)

Quantum Theory and Application of Contextual Optimal Transport. - Nicola Mariella; Albert Akhriev; Francesco Tacchino; Christa Zoufal; Juan Carlos Gonzalez-Espitia; Benedek Harsanyi; Eugene Koskin; Ivano Tavernelli; Stefan Woerner; Marianna Rapsomaniki; Sergiy Zhuk; Jannis Born (ICML, 2024)

Fermionic wave packet scattering: a quantum computing approach. - Yahui Chai; Arianna Crippa; Karl Jansen; Stefan Kühn; Vincent R. Pascuzzi; Francesco Tacchino; Ivano Tavernelli (Quantum, 2025)

Trainability of Quantum Models Beyond Known Classical Simulability. - Sabri Meyer; Francesco Scala; Francesco Tacchino; Aurélien Lucchi (CoRR, 2025)