Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Akhriev, Albert"'
Autor:
Robertson, Niall F., Pokharel, Bibek, Fuller, Bryce, Switzer, Eric, Shtanko, Oles, Amico, Mirko, Byrne, Adam, D'Urbano, Andrea, Hayes-Shuptar, Salome, Akhriev, Albert, Keenan, Nathan, Bravyi, Sergey, Zhuk, Sergiy
Tensor networks and quantum computation are two of the most powerful tools for the simulation of quantum many-body systems. Rather than viewing them as competing approaches, here we consider how these two methods can work in tandem. We introduce a no
Externí odkaz:
http://arxiv.org/abs/2407.17405
Autor:
Mariella, Nicola, Akhriev, Albert, Tacchino, Francesco, Zoufal, Christa, Gonzalez-Espitia, Juan Carlos, Harsanyi, Benedek, Koskin, Eugene, Tavernelli, Ivano, Woerner, Stefan, Rapsomaniki, Marianna, Zhuk, Sergiy, Born, Jannis
Publikováno v:
PMLR 235:34822-34845, 2024
Optimal Transport (OT) has fueled machine learning (ML) across many domains. When paired data measurements $(\boldsymbol{\mu}, \boldsymbol{\nu})$ are coupled to covariates, a challenging conditional distribution learning setting arises. Existing appr
Externí odkaz:
http://arxiv.org/abs/2402.14991
We introduce AQCtensor, a novel algorithm to produce short-depth quantum circuits from Matrix Product States (MPS). Our approach is specifically tailored to the preparation of quantum states generated from the time evolution of quantum many-body Hami
Externí odkaz:
http://arxiv.org/abs/2301.08609
Quantum compilation provides a method to translate quantum algorithms at a high level of abstraction into their implementations as quantum circuits on real hardware. One approach to quantum compiling is to design a parameterised circuit and to use te
Externí odkaz:
http://arxiv.org/abs/2210.09191
Publikováno v:
2022 IEEE International Conference on Quantum Computing and Engineering (QCE), 492-502, 2022
This paper considers the problem of quantum compilation from an optimization perspective by fixing a circuit structure of CNOTs and rotation gates then optimizing over the rotation angles. We solve the optimization problem classically and consider al
Externí odkaz:
http://arxiv.org/abs/2205.04025
Autor:
Marecek, Jakub, Akhriev, Albert
There is an increasing interest in quantum algorithms for optimization problems. Within convex optimization, interior-point methods and other recently proposed quantum algorithms are non-trivial to implement on noisy quantum devices. Here, we discuss
Externí odkaz:
http://arxiv.org/abs/2110.03400
Autor:
Akhriev, Albert, Marecek, Jakub
Publikováno v:
IEEE International Symposium on Multimedia 2019
Many real-world monitoring and surveillance applications require non-trivial anomaly detection to be run in the streaming model. We consider an incremental-learning approach, wherein a deep-autoencoding (DAE) model of what is normal is trained and us
Externí odkaz:
http://arxiv.org/abs/1912.04418
Publikováno v:
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
In tracking of time-varying low-rank models of time-varying matrices, we present a method robust to both uniformly-distributed measurement noise and arbitrarily-distributed ``sparse'' noise. In theory, we bound the tracking error. In practice, our us
Externí odkaz:
http://arxiv.org/abs/1809.03550
This paper describes a new algorithm for solar energy forecasting from a sequence of Cloud Optical Depth (COD) images. The algorithm is based on the following simple observation: the dynamics of clouds represented by COD images resembles the motion (
Externí odkaz:
http://arxiv.org/abs/1710.00194
Publikováno v:
Aquaculture International; Oct2024, Vol. 32 Issue 5, p5603-5623, 21p