Machine Learning Quantum States II
FOCUS · F18 ·
Presentations
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Machine Learning Physics: From Quantum Mechanics to Holographic Geometry
Invited
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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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Comparing deep reinforcement-learning techniques: applications to quantum memory
ORAL
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Presenters
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Petru Tighineanu
- Max Planck Institute for the Science of Light
Authors
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Petru Tighineanu
- Max Planck Institute for the Science of Light
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Thomas Foesel
- Max Planck Institute for the Science of Light
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Talitha Weiss
- IQOQI, University of Innsbruck
- Institute for Quantum Optics and Quantum Information
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Florian Marquardt
- Max Planck Institute for the Science of Light
- Max Planck Institute for the Science of Light, Staudtstrasse 2, 91058 Erlangen, Germany
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Structural Predictors for Machine Learning Modeling of Superconductivity in Iron-based Materials
ORAL
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Presenters
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Valentin Stanev
- University of Maryland, College Park
Authors
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Valentin Stanev
- University of Maryland, College Park
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Jack Flowers
- University of Maryland, College Park
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Ichiro Takeuchi
- Materials Science and Engineering, University of Maryland
- University of Maryland
- University of Maryland, College Park
- Materials Science & Engineering Dept, University of Maryland
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Predicting physical properties of alkanes with neural networks
ORAL
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Presenters
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Pavao Santak
- University of Cambridge
Authors
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Pavao Santak
- University of Cambridge
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Gareth Conduit
- University of Cambridge
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Understanding Magnetic Properties of Uranium-Based Binary Compounds from Machine Learning
ORAL
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Presenters
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Ayana Ghosh
- Materials Science and Engineering, University of Connecticut
Authors
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Ayana Ghosh
- Materials Science and Engineering, University of Connecticut
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Serge M Nakhmanson
- Department of Materials Science and Engineering, University of Connecticut
- Materials Science and Engineering, University of Connecticut
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Jian-Xin Zhu
- Theoretical Division, Los Alamos National Laboratory
- Los Alamos National Laboratory
- Theoretical Division and Center for Integrated Nanotechnologies, Los Alamos National Laboratory
- T4-PHYS OF CONDENSED MATTER & COMPLEX SYS, Los Alamos National Laboratory, Los aAlamos, USA
- CINT, Los Alamos National Laboratory
- Center for Integrated Nanotechnologies, Los Alamos National Laboratory
- Los Alamos National Laboratory,
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Machine learning-assisted search for high performance plasmonic metals
ORAL
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Presenters
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Ethan Shapera
- Department of Physics, University of Illinois at Urbana-Champaign
Authors
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Ethan Shapera
- Department of Physics, University of Illinois at Urbana-Champaign
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Andre Schleife
- University of Illinois at Urbana-Champaign
- Materials Science and Engineering, University of Illinois at Urbana-Champaign
- Department of Materials Science and Engineering, University of Illinois at Urbana-Champaign
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Machine Learning and Crystal Structure Prediction of Molecular Crystals
ORAL
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Presenters
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Emine Kucukbenli
- Condensed Matter Physics, International School for Advanced Studies
- International School for Advanced Studies
Authors
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Ruggero Lot
- International School for Advanced Studies
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Franco Pellegrini
- SISSA, Trieste, Italy
- International School for Advanced Studies
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Yusuf Shaidu
- Condensed Matter Physics, International School for Advanced Studies
- International School for Advanced Studies
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Emine Kucukbenli
- Condensed Matter Physics, International School for Advanced Studies
- International School for Advanced Studies
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Fitting effective models using QMC parameter derivatives
ORAL
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Presenters
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William Wheeler
- University of Illinois at Urbana-Champaign
Authors
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William Wheeler
- University of Illinois at Urbana-Champaign
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Shivesh Pathak
- University of Illinois at Urbana-Champaign
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Lucas Wagner
- Department of Physics, University of Illinois at Urbana-Champaign
- University of Illinois at Urbana-Champaign
- Physics, University of Illinois Urbana-Champaign
- Department of Physics, University of Illinois at Urbana Champaign
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Detection of Phase Transitions in Quantum Spin Chains via Unsupervised Machine Learning
ORAL
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Presenters
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Yutaka Akagi
- Department of Physics, The University of Tokyo
Authors
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Yutaka Akagi
- Department of Physics, The University of Tokyo
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Nobuyuki Yoshioka
- Department of Physics, The University of Tokyo
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Hosho Katsura
- Physics, University of Tokyo
- Department of Physics, University of Tokyo
- University of Tokyo
- Department of Physics, The University of Tokyo
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Supervised learning of phase transitions in classical and quantum systems
ORAL
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Presenters
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Nicholas Walker
- Louisiana State University
Authors
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Nicholas Walker
- Louisiana State University
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Ka-Ming Tam
- Physics, Louisiana State University
- Louisiana State University
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Mark Jarrell
- School of Physics and Astronomy, Louisiana State University
- Physics, Louisiana State University
- Louisiana State University
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