Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Michele Gross"'
Autor:
Sanja Matovic-Miljanovic, Smiljana Cvjetkovic, Vida Stojkovic, Stefan Mandic-Rajcevic, Janko Jankovic, Michele Gross
Publikováno v:
Population Medicine. 5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d66eee70109377b32108b998451de905
https://doi.org/10.18332/popmed/165263
https://doi.org/10.18332/popmed/165263
Autor:
Stefan Mandić-Rajčević, Janko Janković, Smiljana Cvjetković, Vida Jeremić-Stojković, Sanja Matović-Miljanović, Aleksandar Stevanović, Michele Gross
Publikováno v:
Population Medicine. 5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ad539241b28afebc63b84123468356c
https://doi.org/10.18332/popmed/164292
https://doi.org/10.18332/popmed/164292
Autor:
Manuel S. Rudolph, Sacha Lerch, Supanut Thanasilp, Oriel Kiss, Oxana Shaya, Sofia Vallecorsa, Michele Grossi, Zoë Holmes
Publikováno v:
npj Quantum Information, Vol 10, Iss 1, Pp 1-18 (2024)
Abstract Quantum generative models provide inherently efficient sampling strategies and thus show promise for achieving an advantage using quantum hardware. In this work, we investigate the barriers to the trainability of quantum generative models po
Externí odkaz:
https://doaj.org/article/2dd04260c8534dd988845c48f77051cf
Autor:
Vasilis Belis, Kinga Anna Woźniak, Ema Puljak, Panagiotis Barkoutsos, Günther Dissertori, Michele Grossi, Maurizio Pierini, Florentin Reiter, Ivano Tavernelli, Sofia Vallecorsa
Publikováno v:
Communications Physics, Vol 7, Iss 1, Pp 1-11 (2024)
Abstract The ongoing quest to discover new phenomena at the LHC necessitates the continuous development of algorithms and technologies. Established approaches like machine learning, along with emerging technologies such as quantum computing show prom
Externí odkaz:
https://doaj.org/article/11e13b03db654385ae0c69984f5fd614
Publikováno v:
IEEE Transactions on Quantum Engineering, Vol 5, Pp 1-13 (2024)
Recently, quantum computing has been proven as an ideal theory for the design of fuzzy inference engines, thanks to its capability to efficiently solve the rule explosion problem. In this scenario, a quantum fuzzy inference engine (QFIE) was proposed
Externí odkaz:
https://doaj.org/article/7e11bb4e963e4c7ca5f69497eca3046f
Autor:
Federico Raffaele De Filippi, Antonio Francesco Mello, Daniel Sacco Shaikh, Maura Sassetti, Niccolò Traverso Ziani, Michele Grossi
Publikováno v:
Symmetry, Vol 16, Iss 8, p 1078 (2024)
Spin 1/2 quantum spin chains represent the prototypical model for coupled two-level systems. Consequently, they offer a fertile playground for both fundamental and technological applications ranging from the theory of thermalization to quantum comput
Externí odkaz:
https://doaj.org/article/2efc45f09dc84f81bdc69ee57f18e520
Autor:
Alberto Di Meglio, Karl Jansen, Ivano Tavernelli, Constantia Alexandrou, Srinivasan Arunachalam, Christian W. Bauer, Kerstin Borras, Stefano Carrazza, Arianna Crippa, Vincent Croft, Roland de Putter, Andrea Delgado, Vedran Dunjko, Daniel J. Egger, Elias Fernández-Combarro, Elina Fuchs, Lena Funcke, Daniel González-Cuadra, Michele Grossi, Jad C. Halimeh, Zoë Holmes, Stefan Kühn, Denis Lacroix, Randy Lewis, Donatella Lucchesi, Miriam Lucio Martinez, Federico Meloni, Antonio Mezzacapo, Simone Montangero, Lento Nagano, Vincent R. Pascuzzi, Voica Radescu, Enrique Rico Ortega, Alessandro Roggero, Julian Schuhmacher, Joao Seixas, Pietro Silvi, Panagiotis Spentzouris, Francesco Tacchino, Kristan Temme, Koji Terashi, Jordi Tura, Cenk Tüysüz, Sofia Vallecorsa, Uwe-Jens Wiese, Shinjae Yoo, Jinglei Zhang
Publikováno v:
PRX Quantum, Vol 5, Iss 3, p 037001 (2024)
Quantum computers offer an intriguing path for a paradigmatic change of computing in the natural sciences and beyond, with the potential for achieving a so-called quantum advantage—namely, a significant (in some cases exponential) speedup of numeri
Externí odkaz:
https://doaj.org/article/7b1949bdccb94d2cb85449d08f6e2b1f
Publikováno v:
PRX Quantum, Vol 5, Iss 3, p 030314 (2024)
Geometric quantum machine learning based on equivariant quantum neural networks (EQNNs) recently appeared as a promising direction in quantum machine learning. Despite encouraging progress, studies are still limited to theory, and the role of hardwar
Externí odkaz:
https://doaj.org/article/dfe02cb815ae46f580ced6be5c578f1f
Autor:
Büsra Kösoglu-Kind, Robert Loredo, Michele Grossi, Christian Bernecker, Jody M. Burks, Rüdiger Buchkremer
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract Genetic information is encoded as linear sequences of nucleotides, represented by letters ranging from thousands to billions. Differences between sequences are identified through comparative approaches like sequence analysis, where variation
Externí odkaz:
https://doaj.org/article/c003466ca2944fd1b0200397423f2b6f
Publikováno v:
European Physical Journal C: Particles and Fields, Vol 83, Iss 8, Pp 1-19 (2023)
Abstract Extracting longitudinal modes of weak bosons in LHC processes is essential to understand the electroweak-symmetry-breaking mechanism. To that end, we propose a general method, based on wide neural networks, to properly model longitudinal-bos
Externí odkaz:
https://doaj.org/article/77b3ef6328414d0e9d9f76d2bfb769b7