Hsin-Yuan Huang | DeepAI

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Featured Co-authors

Weizhu Chen
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Sitan Chen
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Patrick J. Coles
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Lukasz Cincio
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∙ 05/22/2023

On quantum backpropagation, information reuse, and cheating measurement collapse

The success of modern deep learning hinges on the ability to train neura...

0 Amira Abbas, et al. ∙

∙ 03/22/2023

The power and limitations of learning quantum dynamics incoherently

Quantum process learning is emerging as an important tool to study quant...

0 Sofiène Jerbi, et al. ∙

∙ 03/16/2023

Challenges and Opportunities in Quantum Machine Learning

At the intersection of machine learning and quantum computing, Quantum M...

0 M. Cerezo, et al. ∙

∙ 01/30/2023

Improved machine learning algorithm for predicting ground state properties

Finding the ground state of a quantum many-body system is a fundamental ...

0 Laura Lewis, et al. ∙

∙ 12/12/2022

Hardware-efficient learning of quantum many-body states

Efficient characterization of highly entangled multi-particle systems is...

0 Katherine Van Kirk, et al. ∙

∙ 10/26/2022

Learning to predict arbitrary quantum processes

We present an efficient machine learning (ML) algorithm for predicting a...

0 Hsin-Yuan Huang, et al. ∙

∙ 10/13/2022

The Complexity of NISQ

The recent proliferation of NISQ devices has made it imperative to under...

0 Sitan Chen, et al. ∙

∙ 10/06/2022

Learning many-body Hamiltonians with Heisenberg-limited scaling

Learning a many-body Hamiltonian from its dynamics is a fundamental prob...

0 Hsin-Yuan Huang, et al. ∙

∙ 04/28/2022

Foundations for learning from noisy quantum experiments

Understanding what can be learned from experiments is central to scienti...

0 Hsin-Yuan Huang, et al. ∙

∙ 04/21/2022

Dynamical simulation via quantum machine learning with provable generalization

Much attention has been paid to dynamical simulation and quantum machine...

18 Joe Gibbs, et al. ∙

∙ 04/21/2022

Out-of-distribution generalization for learning quantum dynamics

Generalization bounds are a critical tool to assess the training data re...

8 Matthias C. Caro, et al. ∙

∙ 12/01/2021

Revisiting dequantization and quantum advantage in learning tasks

It has been shown that the apparent advantage of some quantum machine le...

0 Jordan Cotler, et al. ∙

∙ 12/01/2021

Quantum advantage in learning from experiments

Quantum technology has the potential to revolutionize how we acquire and...

11 Hsin-Yuan Huang, et al. ∙

∙ 11/10/2021

Exponential separations between learning with and without quantum memory

We study the power of quantum memory for learning properties of quantum ...

0 Sitan Chen, et al. ∙

∙ 11/10/2021

A Hierarchy for Replica Quantum Advantage

We prove that given the ability to make entangled measurements on at mos...

0 Sitan Chen, et al. ∙

∙ 11/09/2021

Generalization in quantum machine learning from few training data

Modern quantum machine learning (QML) methods involve variationally opti...

21 Matthias C. Caro, et al. ∙

∙ 06/23/2021

Provably efficient machine learning for quantum many-body problems

Classical machine learning (ML) provides a potentially powerful approach...

0 Hsin-Yuan Huang, et al. ∙

∙ 03/12/2021

Efficient estimation of Pauli observables by derandomization

We consider the problem of jointly estimating expectation values of many...

0 Hsin-Yuan Huang, et al. ∙

∙ 01/07/2021

Information-theoretic bounds on quantum advantage in machine learning

We study the complexity of training classical and quantum machine learni...

0 Hsin-Yuan Huang, et al. ∙

∙ 12/16/2020

Nearly tight Trotterization of interacting electrons

We consider simulating quantum systems on digital quantum computers. We ...

0 Yuan Su, et al. ∙

∙ 11/03/2020

Power of data in quantum machine learning

The use of quantum computing for machine learning is among the most exci...

22 Hsin-Yuan Huang, et al. ∙

∙ 07/13/2020

Mixed-state entanglement from local randomized measurements

We propose a method for detecting bipartite entanglement in a many-body ...

0 Andreas Elben, et al. ∙

∙ 02/18/2020

Predicting Many Properties of a Quantum System from Very Few Measurements

Predicting properties of complex, large-scale quantum systems is essenti...

0 Hsin-Yuan Huang, et al. ∙

∙ 09/16/2019

Near-term quantum algorithms for linear systems of equations

Solving linear systems of equations is an essential component in science...

0 Hsin-Yuan Huang, et al. ∙

∙ 08/23/2019

Predicting Features of Quantum Systems using Classical Shadows

Predicting features of complex, large-scale quantum systems is essential...

0 Hsin-Yuan Huang, et al. ∙

∙ 10/06/2018

FlowQA: Grasping Flow in History for Conversational Machine Comprehension

Conversational machine comprehension requires a deep understanding of th...

0 Hsin-Yuan Huang, et al. ∙

∙ 11/16/2017

FusionNet: Fusing via Fully-Aware Attention with Application to Machine Comprehension

This paper introduces a new neural structure called FusionNet, which ext...

0 Hsin-Yuan Huang, et al. ∙

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