Machine Learning Quantum States I
FOCUS · E18
Presentations
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Learning quantum states with generative models
Invited
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Presenters
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Juan Carrasquilla
Vector Institute for Artificial Intelligence, Toronto (Canada), Vector Institute
Authors
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Juan Carrasquilla
Vector Institute for Artificial Intelligence, Toronto (Canada), Vector Institute
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Machine Learning Holography in Neural Network Renormalization Group
ORAL
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Presenters
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Hongye Hu
University of California, San Diego
Authors
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Hongye Hu
University of California, San Diego
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Shuo-Hui Li
Institute of Physics, Chinese Academy of Sciences, Institute of Physics
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Lei Wang
Institute of Physics, Institute of Physics, Chinese Academy of Sciences, Institute of Physics Chinese Academy of Sciences
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Yizhuang You
University of California, San Diego, Department of Physics, Harvard University, Physics, University of California, San Diego, Department of Physics, University of California, San Diego, Harvard University, UCSD
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ABSTRACT WITHDRAWN
COFFEE_KLATCH
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Analytic continuation by combining sparse modeling with the Pade approximation
ORAL
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Presenters
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Yuichi Motoyama
Univ of Tokyo-Kashiwanoha, ISSP, University of Tokyo
Authors
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Yuichi Motoyama
Univ of Tokyo-Kashiwanoha, ISSP, University of Tokyo
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Kazuyoshi Yoshimi
Univ of Tokyo-Kashiwanoha, ISSP, University of Tokyo
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Junya Otsuki
Tohoku University
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Hiroshi Shinaoka
Saitama University
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A machine learning approach to excited states of quantum many-body systems
ORAL
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Presenters
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Douglas Hendry
Northeastern University
Authors
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Douglas Hendry
Northeastern University
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Adrian Feiguin
Physics, Northeastern University, Northeastern University
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Machine Learning Spatial Geometry from Entanglement Features
ORAL
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Presenters
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Yizhuang You
University of California, San Diego, Department of Physics, Harvard University, Physics, University of California, San Diego, Department of Physics, University of California, San Diego, Harvard University, UCSD
Authors
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Yizhuang You
University of California, San Diego, Department of Physics, Harvard University, Physics, University of California, San Diego, Department of Physics, University of California, San Diego, Harvard University, UCSD
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Machine learning many-body localization: Search for the elusive nonergodic metal
ORAL
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Presenters
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Xiao Li
University of Maryland
Authors
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Xiao Li
University of Maryland
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Yi-Ting Hsu
Physics, University of Maryland, College Park, University of Maryland
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Dong-Ling Deng
Institute for Interdisciplinary Information Sciences, Tsinghua University, Tsinghua University, University of Maryland
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Machine learning of condensed-matter phases with physical interpretability
ORAL
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Presenters
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Ming Han
Northwestern University
Authors
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Ming Han
Northwestern University
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Zonghui Wei
Northwestern University
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Erik Luijten
Northwestern University
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Interpretable Machine Learning Study of Many-Body Localization Transition in Disordered Quantum Spin Chains
ORAL
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Presenters
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Wei Zhang
Boston College
Authors
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Wei Zhang
Boston College
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Lei Wang
Institute of Physics, Institute of Physics, Chinese Academy of Sciences, Institute of Physics Chinese Academy of Sciences
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Ziqiang Wang
Department of Physics, Boston College, Boston College, Physics, Boston College
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Analytic continuation via “domain-knowledge free” machine learning
ORAL
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Presenters
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Hongkee Yoon
Department of Physics, KAIST, Department of Physics, Korea Advanced Institute of Science and Technology (KAIST)
Authors
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Hongkee Yoon
Department of Physics, KAIST, Department of Physics, Korea Advanced Institute of Science and Technology (KAIST)
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Jae-Hoon Sim
Department of Physics, KAIST
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Myung Joon Han
Department of Physics, KAIST, Department of Physics, Korea Advanced Institute of Science and Technology (KAIST)
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Monte Carlo Renormalization Group for Systems with Quenched Disorder
ORAL
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Presenters
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Yantao Wu
Princeton University
Authors
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Yantao Wu
Princeton University
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Roberto Car
Princeton University, Chemistry, Princeton University
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