Zobrazeno 1 - 10
of 3 417
pro vyhledávání: '"A. Jerbi"'
Autor:
Bellemare-Pepin, Antoine, Lespinasse, François, Thölke, Philipp, Harel, Yann, Mathewson, Kory, Olson, Jay A., Bengio, Yoshua, Jerbi, Karim
The recent surge in the capabilities of Large Language Models (LLMs) has led to claims that they are approaching a level of creativity akin to human capabilities. This idea has sparked a blend of excitement and apprehension. However, a critical piece
Externí odkaz:
http://arxiv.org/abs/2405.13012
Autor:
Hinsche, Marcel, Ioannou, Marios, Jerbi, Sofiene, Leone, Lorenzo, Eisert, Jens, Carrasco, Jose
Cross-platform verification is the task of comparing the output states produced by different physical platforms using solely local quantum operations and classical communication. While protocols have previously been suggested for this task, their exp
Externí odkaz:
http://arxiv.org/abs/2405.06544
Autor:
Cui, Wenhui, Jeong, Woojae, Thölke, Philipp, Medani, Takfarinas, Jerbi, Karim, Joshi, Anand A., Leahy, Richard M.
To handle the scarcity and heterogeneity of electroencephalography (EEG) data for Brain-Computer Interface (BCI) tasks, and to harness the power of large publicly available data sets, we propose Neuro-GPT, a foundation model consisting of an EEG enco
Externí odkaz:
http://arxiv.org/abs/2311.03764
Autor:
Majumder, Arunava, Krumm, Marius, Radkohl, Tina, Nautrup, Hendrik Poulsen, Jerbi, Sofiene, Briegel, Hans J.
Measurement-based quantum computation (MBQC) offers a fundamentally unique paradigm to design quantum algorithms. Indeed, due to the inherent randomness of quantum measurements, the natural operations in MBQC are not deterministic and unitary, but ar
Externí odkaz:
http://arxiv.org/abs/2310.13524
Autor:
Sweke, Ryan, Recio, Erik, Jerbi, Sofiene, Gil-Fuster, Elies, Fuller, Bryce, Eisert, Jens, Meyer, Johannes Jakob
Quantum machine learning is arguably one of the most explored applications of near-term quantum devices. Much focus has been put on notions of variational quantum machine learning where parameterized quantum circuits (PQCs) are used as learning model
Externí odkaz:
http://arxiv.org/abs/2309.11647
Autor:
Preti, Francesco, Schilling, Michael, Jerbi, Sofiene, Trenkwalder, Lea M., Nautrup, Hendrik Poulsen, Motzoi, Felix, Briegel, Hans J.
Publikováno v:
Quantum 8, 1343 (2024)
Shortening quantum circuits is crucial to reducing the destructive effect of environmental decoherence and enabling useful algorithms. Here, we demonstrate an improvement in such compilation tasks via a combination of using hybrid discrete-continuous
Externí odkaz:
http://arxiv.org/abs/2307.05744
Publikováno v:
Nature Communications 15, 5676 (2024)
Quantum machine learning is often highlighted as one of the most promising practical applications for which quantum computers could provide a computational advantage. However, a major obstacle to the widespread use of quantum machine learning models
Externí odkaz:
http://arxiv.org/abs/2306.00061
Autor:
Jerbi, Sofiene, Gibbs, Joe, Rudolph, Manuel S., Caro, Matthias C., Coles, Patrick J., Huang, Hsin-Yuan, Holmes, Zoë
Quantum process learning is emerging as an important tool to study quantum systems. While studied extensively in coherent frameworks, where the target and model system can share quantum information, less attention has been paid to whether the dynamic
Externí odkaz:
http://arxiv.org/abs/2303.12834
Autor:
Charlotte Maschke, Jordan O’Byrne, Michele Angelo Colombo, Melanie Boly, Olivia Gosseries, Steven Laureys, Mario Rosanova, Karim Jerbi, Stefanie Blain-Moraes
Publikováno v:
Communications Biology, Vol 7, Iss 1, Pp 1-14 (2024)
Abstract Consciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation
Externí odkaz:
https://doaj.org/article/0e60359d5c29489fbfcc4f7cf8ec9235
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-7 (2024)
Abstract Quantum machine learning is often highlighted as one of the most promising practical applications for which quantum computers could provide a computational advantage. However, a major obstacle to the widespread use of quantum machine learnin
Externí odkaz:
https://doaj.org/article/0c143bca09b04e6d85d7e79d20a6718c