Zobrazeno 1 - 10
of 450
pro vyhledávání: '"Campanaro P"'
Encoding optimization for quantum machine learning demonstrated on a superconducting transmon qutrit
Autor:
Cao, Shuxiang, Zhang, Weixi, Tilly, Jules, Agarwal, Abhishek, Bakr, Mustafa, Campanaro, Giulio, Fasciati, Simone D, Wills, James, Shteynas, Boris, Chidambaram, Vivek, Leek, Peter, Rungger, Ivan
Qutrits, three-level quantum systems, have the advantage of potentially requiring fewer components than the typically used two-level qubits to construct equivalent quantum circuits. This work investigates the potential of qutrit parametric circuits i
Externí odkaz:
http://arxiv.org/abs/2309.13036
Autor:
Edoardo Bizzotto, Sofia Fraulini, Guido Zampieri, Esteban Orellana, Laura Treu, Stefano Campanaro
Publikováno v:
Environmental Microbiome, Vol 19, Iss 1, Pp 1-20 (2024)
Abstract Background In recent years, there has been a rapid increase in the number of microbial genomes reconstructed through shotgun sequencing, and obtained by newly developed approaches including metagenomic binning and single-cell sequencing. How
Externí odkaz:
https://doaj.org/article/6f15e8b13dea44fab44cbc79f0e03a0f
Autor:
Anna Santin, Flavio Collura, Garima Singh, Maria Silvia Morlino, Edoardo Bizzotto, Alessandra Bellan, Ameya Pankaj Gupte, Lorenzo Favaro, Stefano Campanaro, Laura Treu, Tomas Morosinotto
Publikováno v:
Biotechnology for Biofuels and Bioproducts, Vol 17, Iss 1, Pp 1-16 (2024)
Abstract Background Microbial biopolymers such as poly-3-hydroxybutyrate (PHB) are emerging as promising alternatives for sustainable production of biodegradable bioplastics. Their promise is heightened by the potential utilisation of photosynthetic
Externí odkaz:
https://doaj.org/article/3b381e6e6fca405694f99a98b6554dc4
Autor:
Campanaro, Luigi, De Martini, Daniele, Gangapurwala, Siddhant, Merkt, Wolfgang, Havoutis, Ioannis
This paper proposes a simple strategy for sim-to-real in Deep-Reinforcement Learning (DRL) -- called Roll-Drop -- that uses dropout during simulation to account for observation noise during deployment without explicitly modelling its distribution for
Externí odkaz:
http://arxiv.org/abs/2304.13150
Autor:
Edoardo Bizzotto, Guido Zampieri, Laura Treu, Pasquale Filannino, Raffaella Di Cagno, Stefano Campanaro
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 2442-2452 (2024)
Bioactive peptides are short amino acid chains possessing biological activity and exerting physiological effects relevant to human health. Despite their therapeutic value, their identification remains a major problem, as it mainly relies on time-cons
Externí odkaz:
https://doaj.org/article/00166a6db57e48008794ae14d9f332ca
Autor:
Cao, Shuxiang, Bakr, Mustafa, Campanaro, Giulio, Fasciati, Simone D., Wills, James, Lall, Deep, Shteynas, Boris, Chidambaram, Vivek, Rungger, Ivan, Leek, Peter
Using quantum systems with more than two levels, or qudits, can scale the computation space of quantum processors more efficiently than using qubits, which may offer an easier physical implementation for larger Hilbert spaces. However, individual qud
Externí odkaz:
http://arxiv.org/abs/2303.04796
Autor:
Elvira Armenio, Andrea Tateo, Francesca Fedele, Nicola Ungaro, Michele Mossa, Vittorio Esposito, Vincenzo Campanaro
Publikováno v:
Oceans, Vol 5, Iss 2, Pp 292-311 (2024)
A coupled numerical approach that combines the WRF model and the Mike 3 (DHI) hydrodynamic model was developed and applied in two semi-enclosed basins in the Ionian Sea (Italy) to assess the wind-driven current. To gain a better understanding of how
Externí odkaz:
https://doaj.org/article/6adc22d00ac942f1b4f1bf0e467ae570
Autor:
Cao, Shuxiang, Lall, Deep, Bakr, Mustafa, Campanaro, Giulio, Fasciati, Simone, Wills, James, Chidambaram, Vivek, Shteynas, Boris, Rungger, Ivan, Leek, Peter
Gate-set tomography (GST) characterizes the process matrix of quantum logic gates, along with measurement and state preparation errors in quantum processors. GST typically requires extensive data collection and significant computational resources for
Externí odkaz:
http://arxiv.org/abs/2210.04857
Publikováno v:
IEEE International Conference on Robotics and Automation (ICRA) 2023
Robotic locomotion is often approached with the goal of maximizing robustness and reactivity by increasing motion control frequency. We challenge this intuitive notion by demonstrating robust and dynamic locomotion with a learned motion controller ex
Externí odkaz:
http://arxiv.org/abs/2209.14887
Training deep reinforcement learning (DRL) locomotion policies often require massive amounts of data to converge to the desired behaviour. In this regard, simulators provide a cheap and abundant source. For successful sim-to-real transfer, exhaustive
Externí odkaz:
http://arxiv.org/abs/2209.12878