Quantum Learning: Efficiency and Scale

Presentations

• AI-Driven Evolutionary Approach for Autonomous Quantum Algorithm Discovery

  ORAL

  March 20, 2026, 12:00 PM – March 20, 2026, 12:12 PM

  Presenters

  • Yuri Alexeev

    • NVIDIA Corporation
    • NVIDIA
    • Argonne National Laboratory

  Authors

  • Yuri Alexeev

    • NVIDIA Corporation
    • NVIDIA
    • Argonne National Laboratory

  • Shuxiang Cao

    • NVIDIA Corporation

  • Kohei Nakaji

    • NVIDIA Corporation

  • Elica Kyoseva

    • NVIDIA Corporation
    • NVIDIA

  View abstract →

• Scaling quantum algorithms via dissipation: avoiding barren plateaus

  ORAL

  March 20, 2026, 12:12 PM – March 20, 2026, 12:24 PM

  Publication: https://arxiv.org/abs/2507.02043

  Presenters

  • Ivan Rojkov

    • ETH Zurich

  Authors

  • Elias Zapusek

    • ETH Zurich

  • Ivan Rojkov

    • ETH Zurich

  • Florentin Reiter

    • ETH Zurich

  View abstract →

• Sample Efficient Inference of Quantum Data

  ORAL

  March 20, 2026, 12:24 PM – March 20, 2026, 12:36 PM

  Presenters

  • Marti Vives

    • Princeton University

  Authors

  • Marti Vives

    • Princeton University

  • Gerasimos M Angelatos

    • Raytheon BBN Technologies

  • Hakan E Tureci

    • Princeton University

  View abstract →

• QuantumBoost: A lazy, yet fast, quantum algorithm for learning with weak hypotheses

  ORAL

  March 20, 2026, 12:36 PM – March 20, 2026, 12:48 PM

  Presenters

  • Amira Abbas

    • Google Quantum AI

  Authors

  • Amira Abbas

    • Google Quantum AI

  • Yanlin Chen

    • University of Maryland

  • Tuyen Nguyen

    • University of Technology Sydney

  • Ronald de Wolf

    • CWI and University of Amsterdam

  View abstract →

• Peaked Generative Learning Models Based on IQP Circuits

  ORAL

  March 20, 2026, 12:48 PM – March 20, 2026, 1:00 PM

  Presenters

  • AFRAD MUHAMED BASHEER

    • IQM Germany GmbH

  Authors

  • AFRAD MUHAMED BASHEER

    • IQM Germany GmbH

  • Thomas Cope

    • IQM Germany GmbH

  • Martin Leib

    • IQM Germany GmbH
    • IQM Qunautm Computers

  View abstract →

• Learning quantum many-body data locally: A provably scalable framework

  ORAL

  March 20, 2026, 1:00 PM – March 20, 2026, 1:12 PM

  Publication: K. Chinzei et al., arXiv:2509.13705

  Presenters

  • Koki Chinzei

    • Fujitsu Limited

  Authors

  • Koki Chinzei

    • Fujitsu Limited

  • Quoc H Tran

    • Fujitsu Limited

  • Norifumi Matsumoto

    • Fujitsu Limited

  • Yasuhiro Endo

    • Fujitsu Limited

  • Hirotaka Oshima

    • Fujitsu Limited
    • Fujitsu Ltd

  View abstract →

• Improved regret bounds for structured online learning of quantum states

  ORAL

  March 20, 2026, 1:12 PM – March 20, 2026, 1:24 PM

  Presenters

  • Jiahui Liu

    • Fujitsu Research of America

  Authors

  • Jiahui Liu

    • Fujitsu Research of America

  • Akshay Bansal

    • Virginia Tech

  View abstract →

• Abstract Withdrawn

  ORAL · Invited · Withdrawn

  March 20, 2026, 1:24 PM – March 20, 2026, 2:00 PM

  View abstract →

• Abstract Withdrawn

  ORAL · Withdrawn

  March 20, 2026, 2:00 PM – March 20, 2026, 2:12 PM

  View abstract →

• Approximating Quantum Ground States via Machine-Learned N-Representability Constraints

  ORAL

  March 20, 2026, 2:12 PM – March 20, 2026, 2:24 PM

  Presenters

  • Ramya Bhaskar

    • Sandia National Laboratories

  Authors

  • Ramya Bhaskar

    • Sandia National Laboratories

  • Andrew Zhao

    • Sandia National Laboratories

  View abstract →

• Physics-Informed Metalearning for Rapid Quantum Device Characterization

  ORAL

  March 20, 2026, 2:24 PM – March 20, 2026, 2:36 PM

  Presenters

  • Arielle Sanford

    • University of Chicago

  Authors

  • Arielle Sanford

    • University of Chicago

  • Andrew T Kamen

    • University of Chicago

  • Frederic T Chong

    • University of Chicago
    • Infleqtion
    • The University of Chicago

  • Andy J Goldschmidt

    • University of Chicago

  View abstract →

• Fermionic-Adapted Shadow Tomography: efficient quantum protocols for estimating dynamical correlation functions

  ORAL

  March 20, 2026, 2:36 PM – March 20, 2026, 2:48 PM

  Publication: arxiv preprint: 2508.03192

  Presenters

  • Taehee Ko

    • Korea Institute for Advanced Study

  Authors

  • Taehee Ko

    • Korea Institute for Advanced Study

  • Mancheon Han

    • Korea Institute for Advanced Study

  • Sangkook Choi

    • Korea Institute for Advanced Study

  View abstract →