Zobrazeno 1 - 10
of 570
pro vyhledávání: '"Cohn, Jeffrey P."'
Addressing the critical shortage of mental health resources for effective screening, diagnosis, and treatment remains a significant challenge. This scarcity underscores the need for innovative solutions, particularly in enhancing the accessibility an
Externí odkaz:
http://arxiv.org/abs/2402.08837
Autor:
Motta, Mario, Kirby, William, Liepuoniute, Ieva, Sung, Kevin J., Cohn, Jeffrey, Mezzacapo, Antonio, Klymko, Katherine, Nguyen, Nam, Yoshioka, Nobuyuki, Rice, Julia E.
Quantum subspace methods (QSMs) are a class of quantum computing algorithms where the time-independent Schrodinger equation for a quantum system is projected onto a subspace of the underlying Hilbert space. This projection transforms the Schrodinger
Externí odkaz:
http://arxiv.org/abs/2312.00178
Gibbs states (i.e., thermal states) can be used for several applications such as quantum simulation, quantum machine learning, quantum optimization, and the study of open quantum systems. Moreover, semi-definite programming, combinatorial optimizatio
Externí odkaz:
http://arxiv.org/abs/2310.20129
Autor:
Wörtwein, Torsten, Allen, Nicholas, Sheeber, Lisa B., Auerbach, Randy P., Cohn, Jeffrey F., Morency, Louis-Philippe
Personalized prediction is a machine learning approach that predicts a person's future observations based on their past labeled observations and is typically used for sequential tasks, e.g., to predict daily mood ratings. When making personalized pre
Externí odkaz:
http://arxiv.org/abs/2306.08149
Autor:
Eassa, Norhan M., Gibbs, Joe, Holmes, Zoe, Sornborger, Andrew, Cincio, Lukasz, Hester, Gavin, Kairys, Paul, Motta, Mario, Cohn, Jeffrey, Banerjee, Arnab
Many-body entangled quantum spin systems exhibit emergent phenomena such as topological quantum spin liquids with distinct excitation spectra accessed in inelastic neutron scattering (INS) experiments. Here we simulate the dynamics of a quantum spin
Externí odkaz:
http://arxiv.org/abs/2304.06146
Variational approaches, such as variational Monte Carlo (VMC) or the variational quantum eigensolver (VQE), are powerful techniques to tackle the ground-state many-electron problem. Often, the family of variational states is not invariant under the r
Externí odkaz:
http://arxiv.org/abs/2302.11588
We propose a class of randomized quantum Krylov diagonalization (rQKD) algorithms capable of solving the eigenstate estimation problem with modest quantum resource requirements. Compared to previous real-time evolution quantum Krylov subspace methods
Externí odkaz:
http://arxiv.org/abs/2211.08274
Publikováno v:
PRX Quantum 2, 040352 (2021)
We demonstrate a method that merges the quantum filter diagonalization (QFD) approach for hybrid quantum/classical solution of the time-independent electronic Schr\"odinger equation with a low-rank double factorization (DF) approach for the represent
Externí odkaz:
http://arxiv.org/abs/2104.08957
Autor:
Rudovic, Ognjen, Tobis, Nicolas, Kaltwang, Sebastian, Schuller, Björn, Rueckert, Daniel, Cohn, Jeffrey F., Picard, Rosalind W.
Standard machine learning approaches require centralizing the users' data in one computer or a shared database, which raises data privacy and confidentiality concerns. Therefore, limiting central access is important, especially in healthcare settings
Externí odkaz:
http://arxiv.org/abs/2101.04800
Critical obstacles in training classifiers to detect facial actions are the limited sizes of annotated video databases and the relatively low frequencies of occurrence of many actions. To address these problems, we propose an approach that makes use
Externí odkaz:
http://arxiv.org/abs/2010.10979