Quantum Learning: Efficiency and Scale

Presentations

• AI-Driven Evolutionary Approach for Autonomous Quantum Algorithm Discovery

  Oral-In-person

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

  Presenters

  • Yuri Alexeev

    • NVIDIA Corporation

  Authors

  • Yuri Alexeev

    • NVIDIA Corporation

  • Shuxiang Cao

  • Kohei Nakaji

  • Elica Kyoseva

  View abstract →

• Scaling quantum algorithms via dissipation: avoiding barren plateaus

  Oral-In-person

  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

  • Ivan Rojkov

    • ETH Zurich

  • Florentin Reiter

    • ETH Zurich

  View abstract →

• Sample Efficient Inference of Quantum Data

  Oral-In-person

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

  Presenters

  • Marti Vives

    • Princeton University

  Authors

  • Marti Vives

    • Princeton University

  • Gerasimos Angelatos

    • Raytheon BBN Technologies

  • Hakan Tureci

    • Princeton University

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

  Oral-In-person

  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

  • Tuyen Nguyen

  • Ronald de Wolf

  View abstract →

• Peaked Generative Learning Models Based on IQP Circuits

  Oral-In-person

  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

  • Martin Leib

  View abstract →

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

  Oral-In-person

  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 Tran

  • Norifumi Matsumoto

  • Yasuhiro Endo

  • Hirotaka Oshima

  View abstract →

• Improved regret bounds for structured online learning of quantum states

  Oral-In-person

  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

  View abstract →

• Robert Wille

  Invited-In-person · Invited · Withdrawn

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

  Presenters

  • Robert Wille

  Authors

  • Robert Wille

  View abstract →

• Exponential Advantage from One More Replica in Estimating Nonlinear Properties of Quantum States

  Oral-In-person · Withdrawn

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

  Publication: arXiv 2509.24000

  Presenters

  • QI YE

    • Tsinghua University

  Authors

  • QI YE

    • Tsinghua University

  • Zhenhuan Liu

    • Tsinghua University

  • Dong-Ling Deng

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

  Oral-In-person

  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

    • University of New Mexico

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• Physics-Informed Metalearning for Rapid Quantum Device Characterization

  Oral-In-person

  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 Kamen

    • University of Chicago

  • Fred Chong

  • Andy Goldschmidt

  View abstract →

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

  Oral-In-person

  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

  • Sangkook Choi

    • Korea Institute for Advanced Study

  View abstract →