no code implementations • 22 Feb 2024 • 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
In cases where paired data measurements ($\mu$, $\nu$) are coupled to a context variable $p_i$ , one may aspire to learn a global transportation map that can be parameterized through a potentially unseen con-text.
no code implementations • 19 Nov 2023 • Isabel Nha Minh Le, Oriel Kiss, Julian Schuhmacher, Ivano Tavernelli, Francesco Tacchino
Our results suggest that molecular force fields generation can significantly profit from leveraging the framework of geometric quantum machine learning, and that chemical systems represent, in fact, an interesting and rich playground for the development and application of advanced quantum machine learning tools.
no code implementations • 25 Jan 2023 • Julian Schuhmacher, Laura Boggia, Vasilis Belis, Ema Puljak, Michele Grossi, Maurizio Pierini, Sofia Vallecorsa, Francesco Tacchino, Panagiotis Barkoutsos, Ivano Tavernelli
Much hope for finding new physics phenomena at microscopic scale relies on the observations obtained from High Energy Physics experiments, like the ones performed at the Large Hadron Collider (LHC).
no code implementations • 8 Apr 2022 • Stefano Mensa, Emre Sahin, Francesco Tacchino, Panagiotis Kl. Barkoutsos, Ivano Tavernelli
Machine Learning (ML) for Ligand Based Virtual Screening (LB-VS) is an important in-silico tool for discovering new drugs in a faster and cost-effective manner, especially for emerging diseases such as COVID-19.
no code implementations • 30 Mar 2022 • Junyu Liu, Khadijeh Najafi, Kunal Sharma, Francesco Tacchino, Liang Jiang, Antonio Mezzacapo
We define wide quantum neural networks as parameterized quantum circuits in the limit of a large number of qubits and variational parameters.
no code implementations • 9 Mar 2022 • Oriel Kiss, Francesco Tacchino, Sofia Vallecorsa, Ivano Tavernelli
Accurate molecular force fields are of paramount importance for the efficient implementation of molecular dynamics techniques at large scales.
no code implementations • 8 Nov 2021 • Junyu Liu, Francesco Tacchino, Jennifer R. Glick, Liang Jiang, Antonio Mezzacapo
We analytically solve the dynamics in the frozen limit, or lazy training regime, where variational angles change slowly and a linear perturbation is good enough.
no code implementations • 3 Mar 2021 • Francesco Tacchino, Stefano Mangini, Panagiotis Kl. Barkoutsos, Chiara Macchiavello, Dario Gerace, Ivano Tavernelli, Daniele Bajoni
In the last few years, quantum computing and machine learning fostered rapid developments in their respective areas of application, introducing new perspectives on how information processing systems can be realized and programmed.
Quantum Physics
1 code implementation • 6 Nov 2018 • Francesco Tacchino, Chiara Macchiavello, Dario Gerace, Daniele Bajoni
Artificial neural networks are the heart of machine learning algorithms and artificial intelligence protocols.
Quantum Physics