Marco Cerezo

Computing exact moments of local random quantum circuits via tensor networks.

[BibT_eX]

[DOI]

,

,

,

Quantum Mach. Intell., December, 2024

Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms?

[BibT_eX]

[DOI]

,

,

,

,

,

Quantum, March, 2024

Random ensembles of symplectic and unitary states are indistinguishable.

[BibT_eX]

[DOI]

,

,

,

CoRR, 2024

Classically estimating observables of noiseless quantum circuits.

[BibT_eX]

[DOI]

Armando Angrisani

,

Alexander Schmidhuber

,

,

,

,

CoRR, 2024

Quantum Convolutional Neural Networks are (Effectively) Classically Simulable.

[BibT_eX]

[DOI]

,

,

,

,

,

CoRR, 2024

Exact spectral gaps of random one-dimensional quantum circuits.

[BibT_eX]

[DOI]

,

,

,

,

CoRR, 2024

Gate-based quantum simulation of Gaussian bosonic circuits on exponentially many modes.

[BibT_eX]

[DOI]

,

,

,

,

CoRR, 2024

Architectures and random properties of symplectic quantum circuits.

[BibT_eX]

[DOI]

Diego García-Martín

,

Paolo Braccia

,

Marco Cerezo

CoRR, 2024

A Review of Barren Plateaus in Variational Quantum Computing.

[BibT_eX]

[DOI]

,

,

,

,

,

,

,

,

,

CoRR, 2024

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

[BibT_eX]

[DOI]

,

,

,

,

Quantum Mach. Intell., December, 2023

Variational Quantum Linear Solver.

[BibT_eX]

[DOI]

,

,

,

,

,

Quantum, November, 2023

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

[BibT_eX]

[DOI]

,

,

,

,

,

,

Quantum, July, 2023

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

[BibT_eX]

[DOI]

,

,

,

,

,

,

Quantum, June, 2023

Subtleties in the trainability of quantum machine learning models.

[BibT_eX]

[DOI]

,

,

,

,

Quantum Mach. Intell., June, 2023

Theory of overparametrization in quantum neural networks.

[BibT_eX]

[DOI]

,

,

,

,

Nat. Comput. Sci., 2023

Does provable absence of barren plateaus imply classical simulability? Or, why we need to rethink variational quantum computing.

[BibT_eX]

[DOI]

,

,

,

,

,

,

,

,

,

,

,

CoRR, 2023

Deep quantum neural networks form Gaussian processes.

[BibT_eX]

[DOI]

Diego García-Martín

,

Martin Larocca

,

Marco Cerezo

CoRR, 2023

On the universality of S<sub>n</sub>-equivariant k-body gates.

[BibT_eX]

[DOI]

Sujay Kazi

,

Martin Larocca

,

Marco Cerezo

CoRR, 2023

Effects of noise on the overparametrization of quantum neural networks.

[BibT_eX]

[DOI]

Diego García-Martín

,

Martin Larocca

,

Marco Cerezo

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]

,

,

,

,

Quantum, September, 2022

Challenges and opportunities in quantum machine learning.

[BibT_eX]

[DOI]

,

,

,

,

Nat. Comput. Sci., 2022

Resource frugal optimizer for quantum machine learning.

[BibT_eX]

[DOI]

,

,

,

,

,

CoRR, 2022

Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networks.

[BibT_eX]

[DOI]

,

,

,

CoRR, 2022

Theory for Equivariant Quantum Neural Networks.

[BibT_eX]

[DOI]

,

,

,

,

,

,

,

CoRR, 2022

Representation Theory for Geometric Quantum Machine Learning.

[BibT_eX]

[DOI]

,

,

,

,

,

,

,

CoRR, 2022

Exponential concentration and untrainability in quantum kernel methods.

[BibT_eX]

[DOI]

,

,

,

CoRR, 2022

Inference-Based Quantum Sensing.

[BibT_eX]

[DOI]

Cinthia Huerta Alderete

,

,

,

,

,

,

CoRR, 2022

Group-Invariant Quantum Machine Learning.

[BibT_eX]

[DOI]

,

,

,

,

,

CoRR, 2022

Covariance matrix preparation for quantum principal component analysis.

[BibT_eX]

[DOI]

,

,

,

CoRR, 2022

Effect of barren plateaus on gradient-free optimization.

[BibT_eX]

[DOI]

,

,

,

,

Quantum, 2021

Generalization in quantum machine learning from few training data.

[BibT_eX]

[DOI]

,

,

,

,

,

,

CoRR, 2021

Entangled Datasets for Quantum Machine Learning.

[BibT_eX]

[DOI]

,

,

,

CoRR, 2021

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

[BibT_eX]

[DOI]

,

,

,

CoRR, 2021

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

[BibT_eX]

[DOI]

,

,

,

,

CoRR, 2021

Connecting ansatz expressibility to gradient magnitudes and barren plateaus.

[BibT_eX]

[DOI]

,

,

,

CoRR, 2021

Variational Quantum Fidelity Estimation.

[BibT_eX]

[DOI]

,

,

,

Quantum, 2020

Variational Quantum Algorithms.

[BibT_eX]

[DOI]

,

,

,

,

,

,

,

,

,

,

CoRR, 2020

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

[BibT_eX]

[DOI]

,

,

,

,

CoRR, 2020

Absence of Barren Plateaus in Quantum Convolutional Neural Networks.

[BibT_eX]

[DOI]

,

,

,

,

,

CoRR, 2020

Noise-Induced Barren Plateaus in Variational Quantum Algorithms.

[BibT_eX]

[DOI]

,

,

,

,

,

,

CoRR, 2020

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

[BibT_eX]

[DOI]

,

,

,

,

,

CoRR, 2020

Trainability of Dissipative Perceptron-Based Quantum Neural Networks.

[BibT_eX]

[DOI]

,

,

,

CoRR, 2020

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

[BibT_eX]

[DOI]

,

,

,

,

CoRR, 2020

Marco Cerezo

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