Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Strahm, Martin"'
Autor:
Landman, Jonas, Mathur, Natansh, Li, Yun Yvonna, Strahm, Martin, Kazdaghli, Skander, Prakash, Anupam, Kerenidis, Iordanis
Publikováno v:
Quantum 6, 881 (2022)
Quantum machine learning techniques have been proposed as a way to potentially enhance performance in machine learning applications. In this paper, we introduce two new quantum methods for neural networks. The first one is a quantum orthogonal neural
Externí odkaz:
http://arxiv.org/abs/2212.07389
Autor:
Cherrat, El Amine, Kerenidis, Iordanis, Mathur, Natansh, Landman, Jonas, Strahm, Martin, Li, Yun Yvonna
Publikováno v:
Quantum 8, 1265 (2024)
In this work, quantum transformers are designed and analysed in detail by extending the state-of-the-art classical transformer neural network architectures known to be very performant in natural language processing and image analysis. Building upon t
Externí odkaz:
http://arxiv.org/abs/2209.08167
Autor:
Kirsopp, Josh John Mellor, Di Paola, Cono, Manrique, David Zsolt, Krompiec, Michal, Greene-Diniz, Gabriel, Guba, Wolfgang, Meyder, Agnes, Wolf, Detlef, Strahm, Martin, Ramo, David Muñoz
We have demonstrated a prototypical hybrid classical and quantum computational workflow for the quantification of protein-ligand interactions. The workflow combines the Density Matrix Embedding Theory (DMET) embedding procedure with the Variational Q
Externí odkaz:
http://arxiv.org/abs/2110.08163
Autor:
Mathur, Natansh, Landman, Jonas, Li, Yun Yvonna, Strahm, Martin, Kazdaghli, Skander, Prakash, Anupam, Kerenidis, Iordanis
Machine Learning provides powerful tools for a variety of applications, including disease diagnosis through medical image classification. In recent years, quantum machine learning techniques have been put forward as a way to potentially enhance perfo
Externí odkaz:
http://arxiv.org/abs/2109.01831
Autor:
Allcock, Jonathan, Vangone, Anna, Meyder, Agnes, Adaszewski, Stanislaw, Strahm, Martin, Hsieh, Chang-Yu, Zhang, Shengyu
Publikováno v:
Frontiers in Drug Discovery, 08 July 2022
Quantum computing for the biological sciences is an area of rapidly growing interest, but specific industrial applications remain elusive. Quantum Markov chain Monte Carlo has been proposed as a method for accelerating a broad class of computational
Externí odkaz:
http://arxiv.org/abs/2105.09690
Autor:
Outeiral, Carlos, Strahm, Martin, Shi, Jiye, Morris, Garrett M., Benjamin, Simon C., Deane, Charlotte M.
Publikováno v:
WIREs Computational Molecular Science, 2020
Quantum computers can in principle solve certain problems exponentially more quickly than their classical counterparts. We have not yet reached the advent of useful quantum computation, but when we do, it will affect nearly all scientific disciplines
Externí odkaz:
http://arxiv.org/abs/2005.12792
Autor:
Outeiral, Carlos, Morris, Garrett M., Shi, Jiye, Strahm, Martin, Benjamin, Simon C., Deane, Charlotte M.
Protein folding is a central challenge in computational biology, with important applications in molecular biology, drug discovery and catalyst design. As a hard combinatorial optimisation problem, it has been studied as a potential target problem for
Externí odkaz:
http://arxiv.org/abs/2004.01118
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