Patrick J. Coles

Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms?

[BibT_eX]

[DOI]

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Quantum, March, 2024

Error Mitigation for Thermodynamic Computing.

[BibT_eX]

[DOI]

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CoRR, 2024

A semi-agnostic ansatz with variable structure for variational quantum algorithms.

[BibT_eX]

[DOI]

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,

Quantum Mach. Intell., December, 2023

Variational Quantum Linear Solver.

[BibT_eX]

[DOI]

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Quantum, November, 2023

The battle of clean and dirty qubits in the era of partial error correction.

[BibT_eX]

[DOI]

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Quantum, July, 2023

Unifying and benchmarking state-of-the-art quantum error mitigation techniques.

[BibT_eX]

[DOI]

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Quantum, June, 2023

Subtleties in the trainability of quantum machine learning models.

[BibT_eX]

[DOI]

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,

Quantum Mach. Intell., June, 2023

Theory of overparametrization in quantum neural networks.

[BibT_eX]

[DOI]

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,

Nat. Comput. Sci., 2023

Thermodynamic Computing System for AI Applications.

[BibT_eX]

[DOI]

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CoRR, 2023

Thermodynamic Matrix Exponentials and Thermodynamic Parallelism.

[BibT_eX]

[DOI]

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CoRR, 2023

Thermodynamic Linear Algebra.

[BibT_eX]

[DOI]

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CoRR, 2023

The power and limitations of learning quantum dynamics incoherently.

[BibT_eX]

[DOI]

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CoRR, 2023

Thermodynamic AI and the fluctuation frontier.

[BibT_eX]

[DOI]

Patrick J. Coles

CoRR, 2023

Diagnosing Barren Plateaus with Tools from Quantum Optimal Control.

[BibT_eX]

[DOI]

Martin Larocca

,

Piotr Czarnik

,

Kunal Sharma

,

Gopikrishnan Muraleedharan

,

Patrick J. Coles

,

Marco Cerezo

Quantum, September, 2022

Non-trivial symmetries in quantum landscapes and their resilience to quantum noise.

[BibT_eX]

[DOI]

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Quantum, September, 2022

Challenges and opportunities in quantum machine learning.

[BibT_eX]

[DOI]

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Nat. Comput. Sci., 2022

Resource frugal optimizer for quantum machine learning.

[BibT_eX]

[DOI]

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CoRR, 2022

Theory for Equivariant Quantum Neural Networks.

[BibT_eX]

[DOI]

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CoRR, 2022

Representation Theory for Geometric Quantum Machine Learning.

[BibT_eX]

[DOI]

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CoRR, 2022

Practical Black Box Hamiltonian Learning.

[BibT_eX]

[DOI]

Andi Gu

,

Lukasz Cincio

,

Patrick J. Coles

CoRR, 2022

Inference-Based Quantum Sensing.

[BibT_eX]

[DOI]

Cinthia Huerta Alderete

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CoRR, 2022

Group-Invariant Quantum Machine Learning.

[BibT_eX]

[DOI]

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CoRR, 2022

Dynamical simulation via quantum machine learning with provable generalization.

[BibT_eX]

[DOI]

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CoRR, 2022

Out-of-distribution generalization for learning quantum dynamics.

[BibT_eX]

[DOI]

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CoRR, 2022

Covariance matrix preparation for quantum principal component analysis.

[BibT_eX]

[DOI]

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,

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CoRR, 2022

The quantum low-rank approximation problem.

[BibT_eX]

[DOI]

Nic Ezzell

,

Zoë Holmes

,

Patrick J. Coles

CoRR, 2022

Error mitigation with Clifford quantum-circuit data.

[BibT_eX]

[DOI]

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,

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Quantum, 2021

Effect of barren plateaus on gradient-free optimization.

[BibT_eX]

[DOI]

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,

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,

Quantum, 2021

Seeking quantum advantage for neural networks.

[BibT_eX]

[DOI]

Patrick J. Coles

Nat. Comput. Sci., 2021

Variational Quantum Algorithms for Semidefinite Programming.

[BibT_eX]

[DOI]

Dhrumil Patel

,

Patrick J. Coles

,

Mark M. Wilde

CoRR, 2021

Generalization in quantum machine learning from few training data.

[BibT_eX]

[DOI]

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CoRR, 2021

Entangled Datasets for Quantum Machine Learning.

[BibT_eX]

[DOI]

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CoRR, 2021

Adaptive shot allocation for fast convergence in variational quantum algorithms.

[BibT_eX]

[DOI]

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CoRR, 2021

Equivalence of quantum barren plateaus to cost concentration and narrow gorges.

[BibT_eX]

[DOI]

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,

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CoRR, 2021

A semi-agnostic ansatz with variable structure for quantum machine learning.

[BibT_eX]

[DOI]

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,

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CoRR, 2021

Long-time simulations with high fidelity on quantum hardware.

[BibT_eX]

[DOI]

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CoRR, 2021

Connecting ansatz expressibility to gradient magnitudes and barren plateaus.

[BibT_eX]

[DOI]

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,

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CoRR, 2021

An Adaptive Optimizer for Measurement-Frugal Variational Algorithms.

[BibT_eX]

[DOI]

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,

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Quantum, 2020

Variational Quantum Fidelity Estimation.

[BibT_eX]

[DOI]

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,

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Quantum, 2020

Variational Quantum Algorithms.

[BibT_eX]

[DOI]

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CoRR, 2020

Optimizing parametrized quantum circuits via noise-induced breaking of symmetries.

[BibT_eX]

[DOI]

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,

,

,

CoRR, 2020

Absence of Barren Plateaus in Quantum Convolutional Neural Networks.

[BibT_eX]

[DOI]

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,

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,

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CoRR, 2020

Noise-Induced Barren Plateaus in Variational Quantum Algorithms.

[BibT_eX]

[DOI]

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CoRR, 2020

Reformulation of the No-Free-Lunch Theorem for Entangled Data Sets.

[BibT_eX]

[DOI]

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CoRR, 2020

Trainability of Dissipative Perceptron-Based Quantum Neural Networks.

[BibT_eX]

[DOI]

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,

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CoRR, 2020

Cost-Function-Dependent Barren Plateaus in Shallow Quantum Neural Networks.

[BibT_eX]

[DOI]

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,

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CoRR, 2020

Quantum Algorithm Implementations for Beginners.

[BibT_eX]

[DOI]

CoRR, 2018

Patrick J. Coles

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