Quantum Information and Learning
ORAL · MAR-A34 · ID: 3108382
Presentations
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Investigation of simple quantum reservoir computers
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Presenters
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Viola Ni
Claremont McKenna College
Authors
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Sarah Marzen
Scripps, Pitzer & Claremont McKenna College
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Kevin Setter
Scripps and Pitzer College
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Viola Ni
Claremont McKenna College
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Learning quantum properties from short-range correlations using multi-task networks
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Publication: arXiv:2310.11807
Presenters
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Ya-Dong Wu
Shanghai Jiao Tong University, Shanghai Jiao Tong Univ
Authors
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Ya-Dong Wu
Shanghai Jiao Tong University, Shanghai Jiao Tong Univ
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Yan Zhu
The University of Hong Kong
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Yuexuan Wang
The University of Hong Kong
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Giulio Chiribella
The University of Hong Kong
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Using variance of gradients to explain quantum phase recognition algorithms
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Presenters
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Nathan A McMahon
Leiden University
Authors
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Nathan A McMahon
Leiden University
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Michael Josef Hartmann
Friedrich-Alexander University Erlangen-Nuremberg
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Petr Zapletal
University of Basel
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Skin effect in quantum neural networks
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Publication: Skin effect in quantum neural networks. arXiv https://arxiv.org/abs/2406.14112 (2024)
Presenters
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Antonio Sannia
IFISC (CSIC-UIB)
Authors
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Antonio Sannia
IFISC (CSIC-UIB)
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Gian Luca Giorgi
Institute for Cross-Disciplinary Physics and Complex Systems (IFISC) UIB-CSIC, IFISC (CSIC-UIB), Institute for Cross-Disciplinary Physics and Complex Systems
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Stefano Longhi
Politecnico di Milano
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Roberta Zambrini
Institute for Cross-Disciplinary Physics and Complex Systems (IFISC) UIB-CSIC, IFISC (CSIC-UIB)
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Entanglement-induced provable and robust quantum learning advantages
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Publication: H. Zhao and D.-L. Deng, "Entanglement-induced provable and robust quantum learning advantages", (2024), arXiv:2410.03094.
Presenters
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Haimeng Zhao
Caltech
Authors
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Haimeng Zhao
Caltech
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Dong-Ling Deng
Tsinghua University
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Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms
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Publication: M. Wanner, L. Lewis, C. Bhattacharyya, D. Dubhashi, A. Gheorghiu. "Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms." Accepted to the 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024).
Presenters
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Laura Lewis
University of Edinburgh
Authors
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Laura Lewis
University of Edinburgh
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Marc Wanner
Chalmers University of Technology
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Chiranjib Bhattacharyya
Indian Institute of Science
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Devdatt Dubhashi
Chalmers University of Technology
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Alexandru Gheorghiu
Chalmers University of Technology
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Characterization of entanglement using a quantum generative adversarial network
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Publication: Quantum Generative Adversarial Networks: Generating and Detecting Quantum Product States<br>JE Steck, EC Behrman<br>arXiv preprint arXiv:2408.12620
Presenters
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Elizabeth C Behrman
Wichita State University
Authors
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Elizabeth C Behrman
Wichita State University
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James E Steck
Wichita State University
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Could we exploit quantum Boltzmann machines for physics-constrained nonlinear regression?
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Presenters
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David D.W. Ren
Quantum Open Source Foundation
Authors
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David D.W. Ren
Quantum Open Source Foundation
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Wael Itani
New York University (NYU)
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Learning from quantum states: thermal states, ground states, and novel architectures
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Publication: Two preprints are in preparation and will be ready by the end of the year. Work started from https://doi.org/10.1063/5.0209201
Presenters
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Stefano Scali
University of Exeter
Authors
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Stefano Scali
University of Exeter
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Oleksandr Kyriienko
University of Exeter
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Chukwudubem Umeano
University of Exeter
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Tackling Quantum Sampling Noise in Quantum Machine Learning on Large-scale Quantum Devices
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Publication: [1] F. Hu, G. Angelatos, S. A. Khan, et al., Phys. Rev. X 13, 041020 (2023)<br>[2] F. Hu, S. A. Khan, et al., Nat. Commun. 15, 7491 (2024)
Presenters
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Fangjun Hu
Princeton University
Authors
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Fangjun Hu
Princeton University
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Marti Vives
Princeton University
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Theodoros Ilias
Princeton University
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Hakan E Tureci
Princeton University
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Learning optical states with quantum computers
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Publication: John Crossman et al 2024 Quantum Sci. Technol. 9 045005
Presenters
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Spencer Douglas Dimitroff
Sandia National Laboratories & University of New Mexico
Authors
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Spencer Douglas Dimitroff
Sandia National Laboratories & University of New Mexico
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Ashe N Miller
Sandia National Laboratories
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John M Kallaugher
Sandia National Laboratories
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Steve M Young
Sandia National Laboratories
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Mohan Sarovar
Sandia National Laboratories
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